Boundary Nodes Research Articles

Boundary node detection in wireless networks with uneven node distribution on open surfaces

Boundary node detection is essential in various application scenarios of wireless networks. However, most previous solutions are only suitable for planar networks with densely and evenly distributed nodes. They cannot satisfy scenarios where nodes are unevenly deployed on open surfaces because the nodes may have different heights, densities, and inter-distances. In this work, we propose a scheme named Surrounding Triangle Validation to detect boundary nodes in wireless networks with uneven node distribution on open surfaces. This solution randomly generates triangles from the 1-hop neighbors of a testing node and validates these triangles. The triangle generation step accepts the triangles with their two endpoints connected by one or more relay nodes in the areas with uneven node density. Then, the generated triangles surrounding the testing node are picked out by point in triangle tests. In the last step, the selected triangles are compared according to the characteristics of a special kind of boundary node to ensure the results of our method. We test our solution in networks with different node densities on several open surfaces. Simulation results show that our method works effectively. It detects boundary nodes more correctly than previous solutions.

Simplified wetting boundary scheme in phase-field lattice Boltzmann model for wetting phenomena on curved boundaries.

In this work, a simplified wetting boundary scheme in the phase-field lattice Boltzmann model is developed for wetting phenomena on curved boundaries. The proposed scheme combines the advantages of the fluid-solid interaction scheme and geometric scheme-easy to implement (no need to interpolate the values of parameters exactly on solid boundaries and find proper characteristic vectors), the value of contact angle can be directly prescribed, and no unphysical spurious mass layer-and avoids mass leakage. Different from previous works, the values of the order parameter gradient on fluid boundary nodes are directly determined according to the geometric formulation rather than indirectly regulated through the order parameters on ghost solid nodes (i.e., ghost contact-line region). For this purpose, two numerical approaches to evaluate the order parameter gradient on fluid boundary nodes are utilized, one with the prevalent isotropic central scheme and the other with a local gradient scheme that utilizes the distribution functions. The simplified wetting boundary schemes with both numerical approaches are validated and compared through several numerical simulations. The results demonstrate that the proposed model has good ability and satisfactory accuracy to simulate wetting phenomena on curved boundaries under large density ratios.

A Novel Geometric Nonlinear Analysis Method for Planar Beam Structures Based on Co- Rotation and Substructure Method

Nonlinear behavior analysis of structures using finite element methods requires multiple iterative solutions. Therefore, improving computational efficiency while ensuring the accuracy of nonlinear calculations is crucial. In this paper, a new geometric nonlinear analysis method for planar beam structures is proposed, based on the co-spinning method and the substructure method, using a substructure containing two planar beam elements as an example. The co-spinning method accurately calculates small deformations by subtracting rigid body displacement from the large displacement of the structure. The substructure method condenses the degrees of freedom of internal nodes into boundary nodes, greatly reducing the order of the nonlinear equilibrium equation group of the structure. The two methods are combined, and a calculation program is developed using the arc length method, which has good performance in solving nonlinear equation groups. Two classic examples are used to verify the correctness of the proposed method by comparing the results with existing literature.

Descriptive forest: experiments on a novel tree-structure-generalization method for describing cardiovascular diseases

BackgroundA decision tree is a crucial tool for describing the factors related to cardiovascular disease (CVD) risk and for predicting and explaining it for patients. Notably, the decision tree must be simplified because patients may have different primary topics or factors related to the CVD risk. Many decision trees can describe the data collected from multiple environmental heart disease risk datasets or a forest, where each tree describes the CVD risk for each primary topic.MethodsWe demonstrate the presence of trees, or a forest, using an integrated CVD dataset obtained from multiple datasets. Moreover, we apply a novel method to an association-rule tree to discover each primary topic hidden within a dataset. To generalize the tree structure for descriptive tasks, each primary topic is a boundary node acting as a root node of a C4.5 tree with the least prodigality for the tree structure (PTS). All trees are assigned to a descriptive forest describing the CVD risks in a dataset. A descriptive forest is used to describe each CVD patient’s primary risk topics and related factors. We describe eight primary topics in a descriptive forest acquired from 918 records of a heart failure–prediction dataset with 11 features obtained from five datasets. We apply the proposed method to 253,680 records with 22 features from imbalanced classes of a heart disease health–indicators dataset.ResultsThe usability of the descriptive forest is demonstrated by a comparative study (on qualitative and quantitative tasks of the CVD-risk explanation) with a C4.5 tree generated from the same dataset but with the least PTS. The qualitative descriptive task confirms that compared to a single C4.5 tree, the descriptive forest is more flexible and can better describe the CVD risk, whereas the quantitative descriptive task confirms that it achieved higher coverage (recall) and correctness (accuracy and precision) and provided more detailed explanations. Additionally, for these tasks, the descriptive forest still outperforms the C4.5 tree. To reduce the problem of imbalanced classes, the ratio of classes in each subdataset generating each tree is investigated.ConclusionThe results provide confidence for using the descriptive forest.

Improving temporal smoothness and snapshot quality in dynamic network community discovery using NOME algorithm.

The goal of dynamic community discovery is to quickly and accurately mine the network structure for individuals with similar attributes for classification. Correct classification can effectively help us screen out more desired results, and it also reveals the laws of dynamic network changes. We propose a dynamic community discovery algorithm, NOME, based on node occupancy assignment and multi-objective evolutionary clustering. NOME adopts the multi-objective evolutionary algorithm MOEA/D framework based on decomposition, which can simultaneously decompose the two objective functions of modularization and normalized mutual information into multiple single-objective problems. In this algorithm, we use a Physarum-based network model to initialize populations, and each population represents a group of community-divided solutions. The evolution of the population uses the crossover and mutation operations of the genome matrix. To make the population in the evolution process closer to a better community division result, we develop a new strategy for node occupancy assignment and cooperate with mutation operators, aiming at the boundary nodes in the connection between the community and the connection between communities, by calculating the comparison node. The occupancy rate of the community with the neighbor node, the node is assigned to the community with the highest occupancy rate, and the authenticity of the community division is improved. In addition, to select high-quality final solutions from candidate solutions, we use a rationalized selection strategy from the external population size to obtain better time costs through smaller snapshot quality loss. Finally, comparative experiments with other representative dynamic community detection algorithms on synthetic and real datasets show that our proposed method has a better balance between snapshot quality and time cost.

Improved radial basis functions mesh deformation based on parallel point selection strategy and incremental LDLT decomposition

Mesh deformation based on radial basis functions (RBF) is widely used in CFD simulations with moving boundaries due to its simplicity, generality, and robustness, among which selecting an optimum reduced set from all boundary nodes is a crucial data reduction step for fewer support points. However, there remains a great need to reduce the computation costs for large-scale mesh. To solve this issue, a parallel point selection strategy and incremental LDLT decomposition method are proposed. With all boundary nodes distributed to all processors on average, the displacements of boundary nodes are calculated at local ones, and the nodes with local maximum error in divergent processors are added to the support point set in parallel. Besides, the matrix decomposition and solution of weight coefficients are conducted with full uses of corresponding results in the last iteration in incremental LDLT decomposition method. The calculation costs of conventional methods and proposed approaches are theoretically analyzed and compared. Three typical test cases of different mesh scales and motion modes are carried out for validation, including the rigid motion of a NACA0012 airfoil, the bending of an ONERA M6 wing, and the pitch of a missile. The results demonstrate that the proposed approaches greatly improve the efficiency of the data reduction procedure compared with the conventional methods, with similar deformation effect represented by support point distribution and deformed mesh quality.

Two-stage stochastic decentralized low-carbon economic dispatch of integrated electricity-gas networks

To achieve low-carbon operation optimization of integrated electricity gas network (IEGN) system with uncertainty, a two-stage stochastic decentralized low-carbon economic scheduling model and its solution method for multi-region interconnection is proposed. Firstly, an IEGN operation cost model considering the stepped carbon emission cost and the benefits of P2G's participation in carbon market transactions is constructed, considering demand-side management (DSM) with user satisfaction and degree of regulation. Secondly, multi-region interconnection is served to overcome single-region space-time limitations with the multi-energy flow, regional decoupling is realized by copying multi-region IEGN boundary nodes, and the scenario method is used to quantify the output uncertainty of IEGN. Hence, a two-stage stochastic optimal scheduling model of multi-region IEGN is established. Then, an improved successive linearization method is proposed for the non-convex transformation. Considering the decentralized autonomy and information privacy of different decision-makers, a decentralized optimization model is established, and the synchronous alternating direction multiplier method (synchronous-ADMM) based on nested improved successive linearization is introduced for the iterative solution. Finally, the feasibility and superiority of the proposed model and algorithm are verified by comparing and analyzing the simulation results of multi-region IEGN under different scenarios and scheduling strategies.

Convexity Hierarchies in Grid Networks

Several algorithms for path planning in grid networks rely on graph decomposition to reduce the search space size; either by constructing a search data structure on the components, or by using component information for A* guidance. The focus is usually on obtaining components of roughly equal size with few boundary nodes each. In this paper, we consider the problem of splitting a graph into convex components. A convex component is characterized by the property that for all pairs of its members, the shortest path between them is also contained in it. Thus, given a source node, a target node, and a (small) convex component that contains both of them, path planning can be restricted to this component without compromising optimality. We prove that it is NP-hard to find a balanced node separator that splits a given graph into convex components. However, we also present and evaluate heuristics for (hierarchical) convex decomposition of grid networks that perform well across various benchmarks. Moreover, we describe how existing path planning methods can benefit from the computation of convex components. As one main outcome, we show that contraction hierarchies become up to an order of magnitude faster on large grids when the contraction order is derived from a convex graph decomposition.

A dynamic large-deformation particle finite element method for geotechnical applications based on Abaqus

In this paper, the application of Abaqus-based particle finite element method (PFEM) is extended from static to dynamic large deformation. The PFEM is based on periodic mesh regeneration with Delaunay triangulation to avoid mesh distortion. Additional mesh smoothing and boundary node smoothing techniques are incorporated to improve the mesh quality and solution accuracy. The field variables are mapped from the old to the new mesh using the closest point projection method to minimize the mapping error. The procedures of the proposed Abaqus-based dynamic PFEM (Abaqus-DPFEM) analysis and its implementation in Abaqus are detailed. The accuracy and robustness of the proposed approach are examined via four illustrative numerical examples. The numerical results show a satisfactory agreement with published results and further confirm the applicability of the Abaqus-DPFEM to solving dynamic large-deformation problems in geotechnical engineering.

Optimal Domain-Partitioning Algorithm for Real-Life Transportation Networks and Finite Element Meshes

For large-scale engineering problems, it has been generally accepted that domain-partitioning algorithms are highly desirable for general-purpose finite element analysis (FEA). This paper presents a heuristic numerical algorithm that can efficiently partition any transportation network (or any finite element mesh) into a specified number of subdomains (usually depending on the number of parallel processors available on a computer), which will result in “minimising the total number of system BOUNDARY nodes” (as a primary criterion) and achieve “balancing work loads” amongst the subdomains (as a secondary criterion). The proposed seven-step heuristic algorithm (with enhancement features) is based on engineering common sense and observation. This current work has the following novelty features: (i) complicated graph theories that are NOT needed and (ii) unified treatments of transportation networks (using line elements) and finite element (FE) meshes (using triangular, tetrahedral, and brick elements) that can be performed through transforming the original network (or FE mesh) into a pseudo-transportation network which only uses line elements. Several examples, including real-life transportation networks and finite element meshes (using triangular/brick/tetrahedral elements) are used (under MATLAB computer environments) to explain, validate and compare the proposed algorithm’s performance with the popular METIS software.

Seismic Response of a Rockfill Dam with an Asphalt–Concrete Core under P Waves with Arbitrary Incident Angles

The incident angles of seismic waves have a significant influence on the seismic response of asphalt–concrete core rockfill dams. This paper constructs the free field of elastic semispace under P waves with arbitrary incident angles and clarifies the variation law of the seismic intensity on the ground surface with incident angles γ and α. The free field on the foundation boundary under arbitrary combinations of angles γ and α are derived according to the wave-field superposition principle. Combined with the viscoelastic artificial boundary, the free field is transformed into the equivalent load on the boundary node, and the input method of the P wave with arbitrary incident angles is established. Finally, the seismic response of the asphalt–concrete core dam under P waves with arbitrary incident angles is studied. The results show that when the incident direction is perpendicular to the dam axis, the dynamic shear stress is the highest, and the local seismic safety factor of the dam is the largest. When the incident direction is parallel to the dam axis, the tensile stress of the asphalt core is the highest, there is a possibility of cracking at the contact part of the lower part of the asphalt core with the canyon, and the seismic subsidence rate of the dam crest is the highest. For the tensile stress of the asphalt core and the dam-crest subsidence rate, the most unfavorable incident angle α is 75° when the incident angle γ is the same.

Evaluation of wing performance for NACA 4415 using subparametric finite element transforms

The goal of the current research is to improve the lift performance of an aerodynamic device for commercial application by performing accurate aerodynamic computations and flow analyses of NACA 4-digit airfoil designs. An enhanced aerodynamic characteristic, which has been estimated effectively by interpreting the impacts of Reynolds numbers at various angles of attack, is crucial for a cost-effective airfoil shape. Numerous Reynolds numbers have been used in the analysis of these aerodynamic properties. Investigations were carried out using subparametric finite elements and a unique approach for higher order triangular element meshing in relation to the NACA 4415 airfoil design. This approach provides precise boundary node information for the airfoil design, resulting in improved calculations of the lift coefficient, drag coefficient, and lift-to-drag ratio. Moreover, it effectively addresses the challenges faced in aerospace research pertaining to flow analysis, thereby reducing the complexities involved. The evaluationof the airfoil shape and analysis for incompressible flow over the NACA 4415 airfoil design could improve the overall effectiveness of the aerodynamic vehicle. Any vehicle's aerodynamic surface must go through a number of tests before being launched. Modern technology can be incorporated into the design process to reduce the high costs associated with these testing processes. The current flow analysis and aerodynamic investigations exhibit a high degree of accuracy, and the use of HO elements lowers the expense of the experiment.

ACA-accelerated hybrid boundary node method applied to multi-domain steady heat conduction problems

This paper presents a fast implementation of the hybrid boundary node method (HBNM) to solve the multi-domain steady heat conduction problems using the Adaptive Cross Approximation (ACA). It is well known that the matrices arising from the discretization of boundary integral equation are fully populated and require special compression techniques for the efficient treatment. The ACA using only few of the original entries for the approximation of the whole matrix is a purely algebraic algorithm which is kernel-independent and easy to be applied directly for various problems. Accelerated by the ACA, several multi-domain steady heat conduction problems have been solved by the HBNM. The results demonstrate the potentials of the ACA-HBNM for solving multi-domain steady heat conduction problems.

Analysis and simulation of a delayed HIV model with reaction–diffusion and sliding control

Selection of an appropriate therapy threshold to restrain the virus load is still challenging on structured treatment interruptions (STIs) for HIV. In this paper, we ponder that how the sliding control and multistability to regulate the treatment effect through comprehensive dynamics of a virus-immune model. Firstly, based on piecewise therapy, we propose a delayed reaction–diffusion virus-immune model under the homogeneous Neumann boundary condition. Secondly, the existence and stabilities of five kinds of equilibria as well as the direction and stability of spatial Hopf bifurcation at regular equilibrium are investigated. Thirdly, the sliding domain and the boundary node bifurcations are addressed by theoretical analysis. Finally, we appraise the effects of therapy threshold, sliding domain and multistability on HIV therapy by simulations, and further seek out the appropriate therapy threshold for infected patients with given physiological parameters and present the corresponding principles. Our explorations will provide evidence for HIV and other disease therapies.

Construction and Calculation Analysis of Mechanical Model of Crushed Rock Pile Treatment of Foundation Earthquake

In recent years, earthquakes have occurred frequently at home and abroad, causing huge losses to the local society. Therefore, it is important to study the mechanical response of foundations under earthquakes. In this paper, firstly, gravel piles are selected as soft ground improvement materials, and A single bulk material pile section and a peripile soil section within the influence of a single pile are considered as a study unit, and the pore water discharge from the consolidation process is equal to the volume reduction of the unit, considering the consolidation deformation of the pile body, the composite foundation consolidation equation is derived, and the consolidation equation is solved by the separation variable method through the isostrain assumption and initial boundary conditions, and the average superporous water pressure of the soil between the body and the pile is obtained. Then, a more realistic non-uniform ground motion input method is adopted, and the seismic fluctuations are converted into equivalent loads on artificial boundary nodes through the Matlab program, and the equivalent loads are applied to the established viscoelastic artificial boundary by OpenSees software to realize ground motion input. Finally, a mechanical analysis model is established by hypothesis, and with the help of mode orthogonal theory and Hilbert yellow transform, the calculation method of ground seismic mechanical response based on non-uniform ground motion input is obtained. The results show that the effect of gravel pile encryption can reduce the accumulation rate and peak of super-static pore pressure during vibration, and the surface settlement of the site is reduced by 40–50% and the surface lateral shift is reduced by 30–50% after encryption; the drainage effect has a significant effect on reducing the accumulation rate of super-static pore pressure and the post-earthquake dissipation time of the soil during vibration, and the surface settlement is reduced by about 10–20% and the lateral shift is reduced by about 30–40% after increasing the drainage effect.

Effects of the hidden errors in the bounce back scheme on the lattice Boltzmann simulation of the turbulent channel flow using the multiple-relaxation-time collision model

In our recent paper [Dong et al., Phys. Fluids 34, 093608 (2022)], it is shown that hidden errors can be introduced by a bounce back scheme at the boundary nodes, due to the fact that it may not be entirely consistent with the Chapman–Enskog approximation of the lattice Boltzmann equation applied to the interior nodes. In this paper, we investigate the effects of these hidden errors on the lattice Boltzmann simulation of the turbulent channel flow with a multiple-relaxation-time (MRT) collision model, extending our previous study using the Bhatnagar–Gross–Krook and two-relaxation-time collision models applied to laminar non-uniform viscous flows. A theoretical framework for identifying the hidden errors in the MRT model is developed, and the hidden errors in two bounce back schemes, namely, the off-wall and on-wall bounce back schemes, are derived in terms of the hydrodynamic variables and relaxation rates. The results reveal several important differences in the expression of hidden errors between the two bounce back schemes. The analysis also points to a correction for the on-wall bounce back scheme when the external force is present. A set of six simulations of the turbulent channel flow, using the two bounce back schemes and three grid resolutions, are, then, performed to demonstrate that the magnitude of the hidden errors can significantly affect the simulated turbulence statistics, the local consistency with the Navier–Stokes equations, and the numerical stability.

Research on Deep Integration of the “Belt and Road” Aviation Network Based on Community Structure from the Perspective of China

Air transport has broad development potential along the “ Belt and Road” by owing to its fast, direct, and comfortable advantages, and the community structure is an important factor determining the efficiency and service functions of the aviation network. The community detection and community structure analysis of the “Belt and Road” aviation network would help to understand the internal relationship of the “Belt and Road” aviation network spatial structure and better integrated and optimized the network. Based on the data of international routes between 522 airports along the “Belt and Road” in 2019, this paper establishes an aviation network model and calculates the degree, average path, clustering coefficient, and centrality index of the “Belt and Road” aviation network. Through Louvain community detection method, 522 airports in the aviation network were divided into four communities, and the structural characteristics and geographical distribution characteristics of the community network were analyzed. The key node identification model in the community is constructed, the hierarchy of each community network is analyzed using the k-core decomposition method, the core node set of the community network is found, the core boundary node set of four aviation community networks is identified, the core node set and core boundary nodes are analyzed repeatedly, and the key node set of the whole network is obtained. Finally, from the perspective of China, a deep integration scheme between Chinese airports, their communities, and other key node sets was proposed. The research found that there are four associations in the “Belt and Road” aviation network: West Asia and North Africa, Russia, Central and Eastern Europe, and China and Southeast Asia. Chinese and Southeast Asian societies rank third among the four societies in terms of scale. They not only have the largest number of key nodes but also the lowest repetition rate of the key nodes. The international airline links in the “Belt and Road” aviation network are more complex. A total of 118 key nodes were identified, of which 83.1% were in the top 20% of overall network centrality.

INVESTIGATION OF STABILITY LOSSES OF THE PACKER WITH A GIRDLE-CYLINDRICAL-CONICAL CONSTRUCTION

In the paper stability losses of the packer with a girdle construction have been investigated by taking into account compactness mechanism. Expanding and constricting cases of conical surface of the packer with a girdle construction have been studied, stability problem of the packer has been solved via numerical estimation by using finite differences method. With this purpose, continuity condition of the deformation has been written for packer construction (cylindrical and conical surface of the packer) and added to stability losses condition. In the first approach the solution has been carried out in boundary and junction nodes of the packer (where cylindrical and conical surfaces combine), however, in the second approach by finite differences method. During packing process stability losses limit has been studied for the first time for a girdle construction. Keywords: packing, well packing, cylindrical-conical construction packing, mode of deformation, critical pressure in packing.

Mesh parameterization using elastic FEM with negative Poisson’s ratio material and triangle shape transformation

Linear mesh parameterization method with a free boundary is an attractive technology and a ubiquitous tool that is widely used in computer graphics and geometry processing. The existing methods always have the shortcoming of element flipping. In this study, a novel linear mesh parameterization method with a free boundary is proposed based on the linear elastic finite element model of a material with negative Poisson’s ratio. With appropriate parameter settings, the method can flatten a 3D mesh without element flipping to the most extent. The proposed method is divided into two steps: (1) each element of the 3D mesh is compressed to the origin point; (2) the degenerated mesh is gradually expanded in a plane under the two forces of equal magnitude and opposite directions based on a finite element model of an elastic membrane material with negative Poisson’s ratio. Subsequently, the causes of element flipping are analyzed at internal nodes and boundary nodes. The triangle shape transformation (TST) method is proposed to solve the problem of internal element flipping, and the stiffness enhancement method is presented to overcome the boundary element flipping caused by the severe mutual extrusion of the internal elements near the boundary. Finally, typical examples are tested to verify the effectiveness of the proposed mesh parameterization method.

Better decision-making strategy with target seeking approach of humanoids using hybridized SOARANN-fuzzy technique

The prediction and decision-making features of the artificial neural network have been applied to several robotic related research works. Humanoid robot navigation is a challenging task for the researchers with best decision making. Simple artificial neural network (ANN) is the connection models which are poor in multistep decision making with long term planning and logical reasoning. So, in this study artificial neural network is improved in long term cognitive planning by SOAR (State Operator and Result) with powerful feature prediction through ANN (SANN) and hybridized with Fuzzy system for generation effective turning angle value, which will guide the humanoids to reach target location with better decision target seeking ability. An intelligent data fusion model is embedded between SOAR and ANN for converting the logical sequence information of SOAR to probabilistic vectors in multilayer ANNs. The obstacle distances are the input parameters to the SANN model and turning angle (TA) is the output from SANN. The obstacle distances along with the TA obtained from SANN is fed to the fuzzy system as input value and effective turning angle (ETA) is obtained to guide the humanoids towards reaching target. The proposed novel technique and ANN is used by both single and multiple humanoids in both simulation and experimental platforms. The novelty of the research focuses on the development of the new SOAR-ANN technique with better decision strategy for effective turning angle value, to obtain global optimal path by avoiding trapping in local optima and dead ends. The simulation and experimental results in terms of path length travelled and time spent to reach target are obtained from both ANN and novel SANN-Fuzzy technique. When the developed novel technique is compared with standalone ANN method during single humanoid navigation then, a significant improvement of 2–5% and 14–15% is observed in related to trajectory path span and trajectory time spent respectively. Similarly, during multiple humanoid navigation percentage improvement of 5–9% and 14–18% is obtained for humanoids in terms of navigational parameters respectively. The results clearly shows the developed technique requires less time and travels less path to reach target as compared to ANN and the percentage of error is also quite low. Statistical analysis is performed from the results of both the techniques and reflects the effectiveness of the proposed technique in comparison to ANN. Further the developed technique is compared against another existing methodologies like Fuzzy-ANN and Boundary Node Approach and, significant enhancements of 5.64% and 9.72% is attained in terms of track span respectively.