Interlayer Connection Research Articles

Numerical and experimental study of energy absorption in multilayer tubes manufactured through spinning forming process under quasi-static axial loading

Currently, dual-layer tubes play a pivotal role in sectors like nuclear, oil, gas, and steam generation. Recent research focuses on enhancing energy absorption in these tubes using the spinning forming process. This thin-walled nature benefits their application as efficient energy absorbers in transportation like trains and aircraft. A novel approach integrates coarse and fine-threaded ridges between steel and aluminum layers to create a mechanical interlock using the spinning forming technique. This interlock enhances the bond through flow forming, resulting in robust dual-layer tubes. Interlayer connection strength is rigorously tested through shear tests, pre and post flow forming, indicating a significant post-flow forming enhancement. This process substantially bolsters the overall structural integrity of dual-layer tubes. In crush tests, both single-layer and dual-layer steel and aluminum tubes undergo pressing through flow forming. Comparative analysis of energy absorption parameters—specific energy and crushing percentage—reveals notable performance differences. An annealed version of the tube with an aluminum layer is also included due to prior aluminum layer failures. Among dual-layer samples, the flow formed variant with fine-threaded ribs exhibits superior energy absorption and bonding. Finite element simulation of the pressed dual-layer sample demonstrates an 8.42 % deviation between simulated and experimental energy absorption outcomes. The study highlights that tightly bonded layers result in enhanced bonding characteristics.

Advanced 3D Printing of Polyetherketoneketone Hydroxyapatite Composites via Fused Filament Fabrication with Increased Interlayer Connection.

Additively manufactured implants, surgical guides, and medical devices that would have direct contact with the human body require predictable behaviour when stress is applied during their standard operation. Products built with Fused Filament Fabrication (FFF) possess orthotropic characteristics, thus, it is necessary to determine the properties that can be achieved in the XY- and Z-directions of printing. A concentration of 10 wt% of hydroxyapatite (HA) in polyetherketoneketone (PEKK) matrix was selected as the most promising biomaterial supporting cell attachment for medical applications and was characterized with an Ultimate Tensile Strength (UTS) of 78.3 MPa and 43.9 MPa in the XY- and Z-directions of 3D printing, respectively. The effect of the filler on the crystallization kinetics, which is a key parameter for the selection of semicrystalline materials suitable for 3D printing, was explained. This work clearly shows that only in situ crystallization provides the ability to build parts with a more thermodynamically stable primary form of crystallites.

Improved Analytic Learned Iterative Shrinkage Thresholding Algorithm and Its Application to Tomographic Synthetic Aperture Radar Building Object Height Inversion

Tomographic Synthetic Aperture Radar (TomoSAR) building object height inversion is a sparse reconstruction problem that utilizes the data obtained from several spacecraft passes to invert the scatterer position in the height direction. In practical applications, the number of passes is often small, and the observation data are also small due to the objective conditions, so this study focuses on the inversion under the restricted observation data conditions. The Analytic Learned Iterative Shrinkage Thresholding Algorithm (ALISTA) is a kind of deep unfolding network algorithm, which is a combination of the Iterative Shrinkage Thresholding Algorithm (ISTA) and deep learning technology, and it has the advantages of both. The ALISTA is one of the representative algorithms for TomoSAR building object height inversion. However, the structure of the ALISTA algorithm is simple, which has neither the excellent connection structure of a deep learning network nor the acceleration format combined with the ISTA algorithm. Therefore, this study proposes two directions of improvement for the ALISTA algorithm: firstly, an improvement in the inter-layer connection of the network by introducing a connection similar to residual networks obtains the Extragradient Analytic Learned Iterative Shrinkage Thresholding Algorithm (EALISTA) and further proves that the EALISTA achieves linear convergence; secondly, there is an improvement in the iterative format of the intra-layer iteration of the network by introducing the Nesterov momentum acceleration, which obtains the Fast Analytic Learned Iterative Shrinkage Thresholding Algorithm (FALISTA). We first performed inversion experiments on simulated data, which verified the effectiveness of the two proposed algorithms. Then, we conducted TomoSAR building object height inversion experiments on limited measured data and used the deviation metric P to measure the robustness of the algorithms to invert under restricted observation data. The results show that both proposed algorithms have better robustness, which verifies the superior performance of the two algorithms. In addition, we further analyze how to choose the most suitable algorithms for inversion in engineering practice applications based on the results of the experiments on measured data.

Comparative analysis of the response of the road structure with full/partial interlayer connection to traffic action

This article investigates the response of the road pavement of a road sector analysed to the action of traffic that was determined numerically by using two dedicated software. In this respect, the Romanian program CALDEROM 2000 (PD 177, 2001), respectively the French program for calculating the road pavements ALIZÉ-LCPC were used. Both programs use the Burminster elastic model for the analytical evaluation of stress states and specific deformations in multilayer road pavements. However, unlike the CALDEROM 2000 program, the ALIZÉ-LCPC software allows the user to define the interfaces between layers and switch loads from single axle to multiple loads, being a rational method, based on the determination of the resilient stresses and deformations in road structures by using the classical linear elastic multilayer model. The aim of this study was to determine whether the road pavement with deficiencies of adhesion between layers is able to take over the calculated traffic considered in the project, possibly the proportion of calculation traffic that can be taken over, which would allow an assessment of the capable operation life of the road pavement and, implicitly, of the possibility of its yielding before the end of the perspective period considered.

Ni-based coating on 5083 aluminum alloy with Cu-Ni interlayer fabricated by ultra-high-speed laser directed energy deposition

Through the innovative design of interlayer connection materials, a high-performance wear-resistant and corrosion-resistant composite protective coating was successfully prepared on the surface of 5083 aluminum alloy using ultra-high-speed (0.5 m/s) laser energy deposition technology. By conducting orthogonal experiments and analyzing the coating morphology and non-destructive testing results, the optimal process parameters for preparing the Cu-Ni25 alloy interlayer and nickel-based alloy surface protection layer were determined. The bond strength and friction resistance of the composite coating and the substrate were tested by shearing and scratch tests. Furthermore, the wear and corrosion resistance of the nickel-based alloy protective layer and substrate were comparatively assessed using an abrasive wear tester, electrochemical workstation, and salt spray test chamber. The results show that the Cu-Ni25 alloy interlayer plays a good bridge role and realizes metallurgical bonding with the aluminum alloy matrix. Additionally, the addition of the nickel-based alloy surface protection layer yields a significant improvement in deformation resistance, wear resistance, and seawater corrosion resistance compared to the aluminum alloy substrate.

Fused filament fabrication of Nylon beyond the glass transition temperature in a thermally-insulated machine

Fused filament fabrication (FFF) is a popular additive manufacturing process by extruding the molten thermoplastic from a nozzle to build an object layer-by-layer. Nylon is an engineering plastic that has good mechanical and chemical properties for assistive devices such as orthoses and prostheses (O&P). Nylon has been successfully applied in FFF of custom O&P. Based on the low glass transition temperature around 50-70℃ of Nylon, an idea to thermally-insulate the build chamber of an FFF machine to raise the temperature in the build volume to above Nylon’s glass transition temperature without additional heating is proposed. Without extensive active heating and cooling, such thermally-insulated FFF machines may achieve cost-effective FFF of custom O&P for practical use. This paper studies this FFF machine concept for FFF of dog bone specimens. The chamber of the FFF machine was thermally insulated. COMSOL Multiphysics® simulation software was adopted to predict the chamber’s temperature level and verified by experimental measurements with eight thermocouples. The effectiveness of the method was validated by the tensile test and microscopic observation of the printed tensile specimens. The strength of the FFF printed tensile specimens with thermally insulated chamber was 26.4% higher than that of the specimens printed at room temperature and close to the annealed FFF specimens. A better interlayer connection was also observed in the specimens FFF printed with the proposed method.

Modeling public opinion dissemination in a multilayer network with SEIR model based on real social networks

Due to the complexity of social relationships, Internet users are active in multiple social networks and receive or release information in various ways and channels. Therefore, the spread of public opinion is not limited to a closed single network. Considering the structural characteristics of WeChat, Weibo and Tiktok, we built a multi-layer network based on the complex network theory. Based on the environmental and personal factors, the calculation methods of transmission rate and immunity rate is proposed. The trends of information transmission in the multi-layer network is simulated through an improved SEIR model. Through simulation, the differences of information transmission between multi-layer networks and single-layer networks are explored, and the impacts of network structure, coupling strength between layers and interlayer connection mode on information transmission are studied. More than 76,000 tweets from 7 events on Weibo are collected to verify the effectiveness of the model and explore the dissemination trends of actual public opinions. Through the research, it is found that (1) the public opinion transmission efficiency of multi-layer network is higher, the scale is larger, and the time is longer. (2) Compared with Weibo and Tiktok, the information transmission in WeChat is more efficient and lasts longer, and promotes the information transmission in the other two networks. (3) With the increase of coupling strength between layers, the efficiency of information transmission becomes higher and the scale becomes larger. This study provides new ideas for the research of public opinion dissemination, and helps relevant departments to correctly guide public opinion.

Target layer state estimation in multilayer complex dynamical networks using functional observability

In large-scale complex dynamical networks, it is significant to estimate the states of target nodes with only a part of measured nodes. Meanwhile, multilayer complex dynamical networks exist widely in society and engineering. Therefore, it has important theoretic meaning and practical value to study the state estimation of target nodes in multilayer complex dynamical networks with limited node measurements. In this paper, with the measurable state information of a portion of nodes in one layer in the multilayer complex dynamical network, the state estimation of target nodes in other layers is studied. First, we build the model of the multilayer complex dynamical network which includes some target nodes and sensor nodes. Second, auxiliary nodes are selected by using the maximum matching principle in graph theory to construct the augmented node set. Third, we discuss the relationship between the minimum number of auxiliary nodes and interlayer connection probability in the multilayer complex dynamical network. Forth, an appropriate functional state observer is designed with limited number of measured nodes according to a typical model-based algorithm. Finally, numerical simulations are given to demonstrate the accuracy of the proposed method. The proposed method can achieve the accurate estimation with less placement of observers and fewer computational costs in the multilayer complex dynamical network.

Damage Detection of Spatial Track–Bridge System with Interlayer Connection Using High-Speed Train Response and Sensitivity Analysis

Bridge damage detection has attracted much attention recently. Most studies on damage detection of the high-speed railway (HSR) bridge neglect the effect of the interlayer connection between the railway track and bridge. This paper proposes a damage detection method for the HSR bridge using response-based sensitivity analysis of high-speed trains. The HSR bridge is modeled as a spatial track–bridge system, in which the fasteners, sleepers and track slabs are modeled as one viscoelastic layer. The responses of multiple vehicles are merged to overcome the critical issue that the length of response data recorded by a high-speed vehicle moving over the bridge is too short to perform the sensitivity analysis. Numerical studies demonstrate that the proposed method is capable to detect damages of the track–bridge system with different train speed, car-body mass, irregularity grade and the interlayer connection properties. By using the signal merging method and the averaged response from multiple train trips, the proposed method is robust to high speed and measurement noise. The damage on the bridge beam and the interlayer connection can be well-identified. It is also found that increasing the car-body mass, damping ratio of the track–bridge system, damping coefficient of interlayer connection could improve the efficiency of damage detection.

Robustness of Consensus of Two-Layer Ring Networks

The topology structure of multi-layer networks is highly correlated with the robustness of consensus. This paper investigates the influence of different interlayer edge connection patterns on the consensus of the two-layer ring networks. Two types of two-layer ring network models are first considered: one is a kind of two-layer ring network with two linked edges between layers (Networks-a), and the other is a kind of two-layer ring network with three linked edges between layers (Networks-b). Using the Laplacian spectrum, the consensus of the network model is derived. The simulation experiments are used to demonstrate the influence of different interlayer edge connection patterns on the consensus of networks. To determine the best edge connection pattern for Networks-a and Networks-b, the number of nodes in a single-layer ring network is denoted by n. The best edge connection pattern for Networks-a is 1 & [(n+2)/2]. Furthermore, n is subdivided into 3k,3k+1,3k+2, and the best edge connection patterns of Networks-b are near 1 & k+1 & 2k+1.

Experimental study of tensile and flexural performances and failure mechanism of none-felt needled composites

None-felt needled composite material is a novel type of composite with excellent interlayer connection performance. Nonetheless, the tensile and flexural properties and failure mechanism have not been clarified. In this work, none-felt needled fabrics and reinforced composites were manufactured, which were then characterized structurally using Micro-CT. Moreover, the tensile and flexural performances were researched with digital image correlation (DIC) technology, and the fracture morphology was observed employing SEM. The results showed that more needled fiber bundles were implanted along the thickness direction, and the fiber diameter and length were increased by 127.2% and 148.2% respectively. The tensile strengths and modulus also enhanced by 31.5% and 32.8%, and the flexural strengths and modulus improved by 13.1% and 26.7%. The tensile and flexural failure modes of none-felt needled composites and conventional felt needled composites consisted of matrix fracture, in-plane fiber pull-out and brittle fracture. Besides, the flexural specimens of none-felt needled composites had a shorter delamination length. The none-felt needled composites with high tensile and flexural performances are expected to be used in key core components such as radome, cabin and skin of hypersonic aircraft.

Over-the-Air Split Machine Learning in Wireless MIMO Networks

In split machine learning (ML), different partitions of a neural network (NN) are executed by different computing nodes, requiring a large amount of communication cost. As over-the-air computation (OAC) can efficiently implement all or part of the computation at the same time of communication, thus by substituting the wireless transmission in the traditional split ML framework with OAC, the communication load can be eased. In this paper, we propose to deploy split ML in a wireless multiple-input multiple-output (MIMO) communication network utilizing the intricate interplay between MIMO-based OAC and NN. The basic procedure of the OAC split ML system is first provided, and we show that the inter-layer connection in a NN of any size can be mathematically decomposed into a set of linear precoding and combining transformations over a MIMO channel carrying out multi-stream analog communication. The precoding and combining matrices which are regarded as trainable parameters, and the MIMO channel matrix, which are regarded as unknown (implicit) parameters, jointly serve as a fully connected layer of the NN. Most interestingly, the channel estimation procedure can be eliminated by exploiting the MIMO channel reciprocity of the forward and backward propagation, thus greatly saving the system costs and/or further improving its overall efficiency. The generalization of the proposed scheme to the conventional NNs is also introduced, i.e., the widely used convolutional NNs. We demonstrate its effectiveness under both the static and quasi-static memory channel conditions with comprehensive simulations.

Membership-Mismatched Impulsive Exponential Stabilization for Fuzzy Unconstrained Multilayer Neural Networks With Node-Dependent Delays

This article focuses on the membership-mismatched impulsive exponential stabilization for fuzzy unconstrained multilayer neural networks (MNNs) with node-dependent time-varying delays (NDTVDs). To begin with, this work proposes a novel MNNs model with unconstrained interlayer and intralayer parameters, which may allow nodes in all layers to have inconsistent attributes and structures. Meanwhile, the novel model considers the NDTVDs and removes the strict constraints including node alignment and one-to-one interlayer connection to meet diverse modeling requirements in complex applications. Then, the proposed fuzzy impulsive controller does not need to share the same fuzzy parameters as the fuzzy MNNs model, reducing the implementation complexity of the fuzzy impulsive controller. To derive the main results using the augmented vector form of unconstrained MNNs, the sparse matrix method is proposed to convert the node-dependent delayed MNNs model into an equivalent model with multiple delays. Moreover, the time-dependent Lyapunov function (TDLF) technique is adopted to improve the reliability of the stabilization conditions by fully utilizing the state information of both the current and neighboring impulsive intervals. Finally, the main results are verified using numerical simulation.

Occurrence of super-diffusion in two-layer networks.

Super-diffusion is a phenomenon that can be observed in multilayer networks, which describes that the diffusion in a multilayer network is faster than that in the fastest individual layer. In most studies of super-diffusion on two-layer networks, many researchers have focused on the overlap of edges in the two layers and the mode of interlayer connectivity. We discover that the occurrence of super-diffusion in two-layer networks is not necessarily related to the overlap degree. In particular, in a two-layer network, sparse topological structures of individual layers are more beneficial to the occurrence of super-diffusion than dense topological structures. Additionally, similar diffusion abilities of both layers favor super-diffusion. The density of interlayer edges and interlayer connection patterns also influence the occurrence of super-diffusion. This paper offers suggestions to improve the diffusion ability in two-layer networks, which can facilitate the selection of practical information transmission paths between different systems and optimize the design of the internal framework of a company composed of multiple departments.

Dynamic event-triggered control for intra/inter-layer synchronization in multi-layer networks

In this paper, intra-layer synchronization (ALS) and inter-layer synchronization (RLS) of multi-layer networks (MLNs) are studied, where the topology of each layer is different and the inter-layer connection is node-to-node if two layers are connected. Dynamic event-triggered (DET) control is first introduced into the design of synchronization controllers in MLNs to reduce communication frequency. Based on the Lyapunov functional method, sufficient conditions for ALS and RLS are strictly derived by designing appropriate DET controllers. It is theoretically verified that the designed DET conditions in MLNs further reduce triggering frequency compared with static event-triggered (SET) conditions, and Zeno phenomenon can be eliminated. Finally, the validity of the theoretical results is illustrated by numerical simulations.

Expanding the capabilities of laser-based powder bed fusion of polymers through the use of electrophotographic powder application

Generating multimaterial parts, reaching higher efficiency in powder consumption, and decoupling of powder application behavior from powder properties such as powder flowability are key aspects for using electrophotographic powder application (EPA) in laser-based powder bed fusion of polymers (PBF-LB/P). Moreover, EPA allows the layer thickness to be reduced from around 100–150 μm, depending on respective particle size distribution, in the case of conventional doctor blade or roller-based powder application methods to the diameter of the applied polymer particles (typically between 50 and 130 μm). This can have positive effects on the interlayer connection and, therefore, the mechanical properties of the additively manufactured part because less powder volume has to be fused with the already generated underlying part. Moreover, due to the above-mentioned independence of EPA from powder flowability, the addition of flow aids, such as nano silica, can be reduced to a minimum or even avoided completely. This is the first comprehensive study on resulting properties of parts generated by PBF-LB/P using EPA taking into account both the reduction in layer thickness and reduced addition of flow aids. In addition to improving mechanical properties of generated parts, the independence of powder flowability, in particular, offers the possibility of qualifying currently unsuitable materials for PBF-LB/P. For this purpose, besides widely employed polyamide 12 (PA12), a polypropylene (PP) powder is used that is very difficult to process in conventional PBF-LB/P and can only be applied there with the help of flow aids.

Study on Cascading Failure and Elasticity of UAV Swarm Communication Network

As an important new force in information warfare, the UAV swarm has attracted more and more attention from militarists and scholars of various countries. At present, large-scale and low-cost UAV swarms have been gradually applied to reconnaissance operations. The invulnerability and elasticity of its communication network are the key factors that determine whether the swarm can successfully complete the reconnaissance mission. The research object of this study is the UAV swarm communication network, which performs reconnaissance missions. The swarm network is extracted as a three-layer interdependent network model. We apply scale-free network theory and the new connection probability equation to establish three subnetworks. Then, a three-layer interdependent network is constructed by using the interlayer connection rules of the nodes with the largest degree. The classical M-L model is extended to an interdependent network. An interlayer load redistribution rule is proposed to simulate the cascading failure process of swarm networks. Then, we attack network nodes randomly and observe the invulnerability and elasticity of this network. The simulation results show that the performance of the interdependent network is better than that of the single-layer network due to the effect of the interdependent links. By analyzing the experimental results, some feasible suggestions are put forward to improve the invulnerability and elasticity of reconnaissance UAV swarm communication network.

Failure mode of interlayer connection of longitudinally-connected ballastless track-bridge system under uneven pier settlement

• Proposing the characterization model of uneven pier settlement and interlayer connection failure in LBTBS. • Analysing the generation mechanism and development law of interlayer connection failure caused by uneven pier settlement. • Describing the evolution law of interlayer contact behavior of each layer of track caused by uneven pier settlement considering the existing interlayer connection failure. The generation and mechanical balance mechanisms and the deformation compatibility relationship of interlayer connection failure (ICF) of a longitudinally-connected ballastless track-bridge system (LBTBS) caused by uneven pier settlement is analyzed in this paper. The characterization model of the uneven pier settlement and the ICF of the LBTBS was derived based on Castigliano's Second Theorem, Linear Superposition principle, Heaviside function, and Tension-free Winkler beam. The characterization model was further verified by the field measured data and finite element model results. Finally, the development law of the ICF of the LBTBS caused by uneven pier settlement based on the characterization model was analyzed. The results show that the calculated results of the characterization model agree well with the field measured data and finite element model results, which verifies the correctness of the characterization model. Under uneven pier settlement, a void beneath the slab first appeared between the base slab and bridge, and then mortar debonding occurred between the CA mortar and track/base slab when settlement value is 193.48 mm. The maximum height of void beneath the slab developed away from the beam gap, and when the settlement value was less than 8.434 mm, the void beneath the slab length in the left area of the settlement pier was greater than that of the adjacent pier. With the increase in mileage, the height of the void beneath the slab and mortar debonding increased first and then decreased. In practical engineering, mortar debonding is not easy to notice, and the void beneath the slab between the base slab and the bridge should be inspected regularly. The existing fastener failure had little influence on developing a void beneath the slab caused by the uneven pier settlement. The existing mortar void aggravated the occurrence of mortar debonding. When the existing mortar void length exceeded 5 m, the mortar debonding length at both ends of the adjacent pier was about 1/2 of the existing mortar void length. When the length of the existing mortar void was less than 1 m, there was little effect on the length of the void beneath the slab.

Enhanced support effects in single-atom copper-incorporated carbon nitride for photocatalytic suzuki cross-coupling reactions

Conditioning the nature of metal active sites for better performance by well designing and constructing the support material is always appealing in heterogeneous catalysis. Herein, Cu species was introduced into the bulk phase of carbon nitride to strengthen the interlayer connection and optimize the electronic structure. The resulting material (CN-Cu) demonstrated an enhanced support effect for Pd catalyzed Suzuki cross-coupling reactions under light illumination. Detailed characterizations showed that Cu species were atomically incorporated in intra/interlayer of CN framework through coordinating with pyridinic nitrogen, leading to improved light absorption and more efficient charge carrier transfer. More importantly, the electronic effect of CN-Cu to the surface Pd was enhanced by the electron drift from Cu to N, thereby rendered an electron-rich Pd surface. Such Pd surfaces allowed faster electron injection from Pd(0) to the LUMO of aryl halides and therefore accelerate the rate-determining step of the coupling reaction.

Analytical Procedure for Timber−Concrete Composite (TCC) System with Mechanical Connectors

In the construction of modern multi-storey mass timber structures, a composite floor system commonly specified by structural engineers is the timber–concrete composite (TCC) system, where a mass timber beam or mass timber panel (MTP) is connected to a concrete slab with mechanical connectors. The design of TCC floor systems has not been addressed in timber design standards due to a lack of suitable analytical models for predicting the serviceability and safety performance of these systems. Moreover, the interlayer connection properties have a large influence on the structural performance of a TCC system. These connection properties are often generated by testing. In this paper, an analytical approach for designing a TCC floor system is proposed that incorporates connection models to predict connection properties from basic connection component properties such as embedment and withdrawal strength/stiffness of the connector, thereby circumventing the need to perform connection tests. The analytical approach leads to the calculation of effective bending stiffness, forces in the connectors, and extreme stresses in concrete and timber of the TCC system, and can be used in design to evaluate allowable floor spans under specific design loads and criteria. An extensive parametric analysis was also conducted following the analytical procedure to investigate the TCC connection and system behaviour. It was observed that the screw spacing and timber thickness remain the most important parameters which significantly influence the TCC system behaviour.