Multi-layer Joint Research Articles

Digital Self-Interference Canceler with Joint Channel Estimator for Simultaneous Transmit and Receive System.

Simultaneous transmit and receive wireless communications have been highlighted for their potential to double the spectral efficiency. However, it is necessary to mitigate self-interference (SI). Considering both the SI channel and remote transmission (RT) channel need to be estimated before equalizing the received signal, we propose two adaptive algorithms for linear and nonlinear self-interference cancellation (SIC), based on a multi-layered joint channel estimator structure. The proposed algorithms estimate the RT channel while performing SIC, and the multi-layered structure ensures improved performance across various interference-to-signal ratios. The M-estimate function enhances the robustness of the algorithm, allowing it to converge even when affected by impulsive noise. For nonlinear SIC, this paper introduces an adaptive algorithm based on generalized Hammerstein polynomial basis functions. The simulation results indicate that this approach achieves a better convergence speed and normalized mean squared difference compared to existing SIC methods, leading to a lower system bit error rate.

A Multilayer Joint Regularized Block Sparse Bayesian Algorithm with Space-Time Structured Prior Learning Function

A Multilayer Joint Regularized Block Sparse Bayesian Algorithm with Space-Time Structured Prior Learning Function

Dynamic interwell connectivity analysis of multi-layer waterflooding reservoirs based on an improved graph neural network

The analysis of interwell connectivity plays an important role in the formulation of oilfield development plans and the description of residual oil distribution. In fact, sandstone reservoirs in China's onshore oilfields generally have the characteristics of thin and many layers, so multi-layer joint production is usually adopted. It remains a challenge to ensure the accuracy of splitting and dynamic connectivity in each layer of the injection-production wells with limited field data. The three-dimensional well pattern of multi-layer reservoir and the relationship between injection-production wells can be equivalent to a directional heterogeneous graph. In this paper, an improved graph neural network is proposed to construct an interacting process mimics the real interwell flow regularity. In detail, this method is used to split injection and production rates by combining permeability, porosity and effective thickness, and to invert the dynamic connectivity in each layer of the injection-production wells by attention mechanism. Based on the material balance and physical information, the overall connectivity from the injection wells, through the water injection layers to the production layers and the output of final production wells is established. Meanwhile, the change of well pattern caused by perforation, plugging and switching of wells at different times is achieved by updated graph structure in spatial and temporal ways. The effectiveness of the method is verified by a combination of reservoir numerical simulation examples and field example. The method corresponds to the actual situation of the reservoir, has wide adaptability and low cost, has good practical value, and provides a reference for adjusting the injection-production relationship of the reservoir and the development of the remaining oil.

Block-Wise Index Modulation and Receiver Design for High-Mobility OTFS Communications

As a promising technique for high-mobility wireless communications, orthogonal time frequency space (OTFS) has been proved to enjoy excellent advantages with respect to traditional orthogonal frequency division multiplexing (OFDM). Although multiple studies have considered index modulation (IM) based OTFS (IM-OTFS) schemes to further improve system performance, a challenging and open problem is the development of effective IM schemes and efficient receivers for practical OTFS systems that must operate in the presence of channel delays and Doppler shifts. In this paper, we propose two novel block-wise IM schemes for OTFS systems, named delay-IM with OTFS (DeIM-OTFS) and Doppler-IM with OTFS (DoIM-OTFS), where a block of delay/Doppler resource bins are activated simultaneously. Based on a maximum likelihood (ML) detector, we analyze upper bounds on the average bit error rates for the proposed DeIM-OTFS and DoIM-OTFS schemes, and verify their performance advantages over the existing IM-OTFS systems. We also develop a multi-layer joint symbol and activation pattern detection (MLJSAPD) algorithm and a customized message passing detection (CMPD) algorithm for our proposed DeIM-OTFS and DoIM-OTFS systems with low complexity. Simulation results demonstrate that our proposed MLJSAPD and CMPD algorithms can achieve desired performance with robustness to the imperfect channel state information (CSI).

Failure mechanism of parallel gap resistance welding joint between Ag foil and GaAs solar cell by temperature cycling

Reliability of joints in solar arrays significantly influences the service life of satellites. Interface between solar cell and interconnector experiences serious temperature cycling during space service which would further lead to failure. To further improve the interface joining thermal reliability, elucidation of the interface formation and corresponding microstructure evolution during thermal fatigue is necessary. In this study, parallel gap resistance welded (PGRW) multi-layered joint between GaAs solar cell and Ag foil are subjected to different temperature cycling tests (−160–120 °C, −165–160 °C) with various cycles. Obtained results confirm the joining mechanism of the joint as solid-solution interdiffusion between Ag foil and Au surface of solar cell electrode. Also, conducted temperature cycling essentially lead to thermal fatigue process at Ag/Au interface, therefore more serious interface strength degradation is generated by larger temperature cycling range. Joint failure is initiated by thermal fatigue induced dislocation and residual strain concentrations around dissimilar interface. And the large mismatch in coefficients of thermal expansion (CTE) of the multilayer structure amplifies the thermal fatigue effect.

A method for the reproducible and accurate determination of electrical resistances based on multi-layer joints in lithium-ion batteries

The transition from fossil fuels to renewable energy sources is significantly influenced by the development of energy storage systems such as batteries. One of the crucial steps in the production of lithium-ion batteries is the electrical connection of the individual electrodes by weld seams. Various joining processes, such as laser beam welding or ultrasonic metal welding, are used for this purpose. An important quality feature of the connections is a low electrical joint resistance, which is essential for reducing cell-internal energy losses and avoiding thermal inhomogeneities in the cells.The aim of this work was to determine the electrical resistance of the joint between a stack of foils and an arrester tab. For this purpose, a measuring method was developed and applied to different sample configurations. The influence of different probe tips on the measurement results was compared using single current collector foils and arrester tabs. The measurement of the electrical resistance was possible in the considered range with a maximum relative uncertainty of 2.38%. Using the presented approach made it possible to evaluate the influence of the seam trajectory on the electrical resistance for cell-internal contacting. In addition, the measuring method is suitable for comparing different welding strategies and, thus, for designing the cell-internal joining processes regarding the resulting electrical joint resistances.

A comprehensive study of parallel gap resistance welding joint between Ag foil and front electrode of GaAs solar cell

When space solar cell array is subjected to harsh temperature cycle, such as planet orbit, thermal fatigue cracks in bonding area are easily induced. With the aim of improving bonding quality and elucidating failure mechanism of parallel gap resistance welding (PGRW) joints in temperature cycling environment, the present research investigates the effect of current density on bonding quality and thermal fatigue behavior of PGRW joint between Ag interconnector and front electrode of GaAs solar cell. When current density is set at 417 A/mm2, a solid diffusion bonding is achieved at the Ag/Au interface, which also possesses adequate joint strength as ensured by both pressure and input energy of PGRW. Crack initiation by thermal fatigue is found at joint edge, which subsequently propagates along the interface as the environment temperature cycling continues. Further investigation reveals that the conducted temperature cycling generates serious tensile and compressive stress in the multi-layered joint structure. Since such reciprocating forces directly induce micro-plastic deformation and strain accumulation at joint interface, failure by crack is finally generated at the joining interface.

On the mechanics of a double thin film on a finite thickness substrate

The single edge loading problem of a double thin film deposited on a finite thickness substrate is considered. The films and the substrate are assumed to be homogeneous and isotropic. The membrane analogy is adopted for the films and two dimensional elasticity is applied to the substrate. The compatibility of the tangential strain between the film and the substrate yields the governing singular integral equation in terms of the interfacial shear stress. The numerical solution is provided using the Gauss–Chebyshev discretization method. The sensitivity of the interfacial shear and the normal stresses to several effective parameters are examined. The results of current study are compatible with the finite element simulations. The lowest interfacial shear stress pertains to a substrate with a free edge boundary condition. The results of current study are applicable to the debonding failure assessment of the multi-layer joints and semiconductors which are susceptible to the interfacial shear stresses near the film edges.

Multilayer Joint Optimization of Packet Size and Adaptive Transmission Scheduling of Wireless Sensor Networks for Mechanical Vibration Monitoring

Limitations pertaining to the storage capacity and bandwidth of wireless sensor networks (WSNs) for mechanical vibration monitoring (MVM) pose difficulties in the realization of reliable and energy-efficient communication of big data. To prolong the lifetime of battery-limited WSNs, this paper proposes a multi-layer joint optimization of packet size and adaptive transmission scheduling (ATS) to jointly optimize the energy consumption of acquisition nodes from the storage and transmission layers. First, owing to the frequent storage and transmission of massive mechanical vibration data in WSNs, the packet size significantly affects the energy consumption during storage and transmission. The proposed packet size optimization based on the lowest energy consumption (PSO-LEC) model optimizes the energy consumption of acquisition nodes from three aspects: writing, reading, and transmission of data. Second, when transmitting massive vibration data frequently, the direct beacon frame conflict and indirect beacon frame conflict markedly induce data conflict and delay problems. Therefore, adaptive transmission scheduling based on the time division multiple access (TDMA/ATS) method is proposed to optimize the errors in data collision and transmission delay. Thus, the packet size and ATS are considered jointly to improve the network lifetime for MVM. Comprehensive experimental results indicate that the transmission reliability and energy-efficiency of the proposed scheme are significantly improved, and the network life is effectively prolonged for MVM.

Inferring cancer common and specific gene networks via multi-layer joint graphical model

Cancer is a complex disease caused primarily by genetic variants. Reconstructing gene networks within tumors is essential for understanding the functional regulatory mechanisms of carcinogenesis. Advances in high-throughput sequencing technologies have provided tremendous opportunities for inferring gene networks via computational approaches. However, due to the heterogeneity of the same cancer type and the similarities between different cancer types, it remains a challenge to systematically investigate the commonalities and specificities between gene networks of different cancer types, which is a crucial step towards precision cancer diagnosis and treatment. In this study, we propose a new sparse regularized multi-layer decomposition graphical model to jointly estimate the gene networks of multiple cancer types. Our model can handle various types of gene expression data and decomposes each cancer-type-specific network into three components, i.e., globally shared, partially shared and cancer-type-unique components. By identifying the globally and partially shared gene network components, our model can explore the heterogeneous similarities between different cancer types, and our identified cancer-type-unique components can help to reveal the regulatory mechanisms unique to each cancer type. Extensive experiments on synthetic data illustrate the effectiveness of our model in joint estimation of multiple gene networks. We also apply our model to two real data sets to infer the gene networks of multiple cancer subtypes or cell lines. By analyzing our estimated globally shared, partially shared, and cancer-type-unique components, we identified a number of important genes associated with common and specific regulatory mechanisms across different cancer types.

Star Identification Algorithm Based on Multi-Dimensional Features and Multi-Layered Joint Screening for Star Sensors

Star Identification Algorithm Based on Multi-Dimensional Features and Multi-Layered Joint Screening for Star Sensors

Effects of lap configuration on mechanical properties and composition distribution of three-layer overlapped laser weldments on Al/Cu dissimilar materials

Battery cells are connected via bus-bars to meet performance requirements, such as power and capacity, and multiple layers of dissimilar materials functioning as anodes, cathodes, or bus-bars are overlapped and welded together. In laser welding, the formation of brittle intermetallic phases in the weld joint is inevitable and, in turn, deteriorates the mechanical properties. To obtain the desirable joint performance, appropriate welding parameters to avoid intermetallic phase formations and joint designs to release stress concentrations must be obtained. This study investigates the effects of lap configurations and process parameters on the tensile-shear load, T-peel load, and composition distribution when multi-layered joints of dissimilar materials are produced by laser welding. Two layers of 0.4 mm Al sheets were welded with a single 0.2 mm Cu sheet, which was emulated using electric vehicle battery interconnects. The results show that the penetration depth varied in accordance with the lap configuration even under the same heat input condition. The lap configuration and welding parameters influenced the composition distribution of the welds, as they altered the solidification rate, number of Cu/Al contact interfaces, and location of the high-density material. The failure load of the T-peel specimens was lower than that of the tensile-shear specimens except for the Cu − Al − Al lap configuration. The T-peel load of the Cu − Al − Al lap configuration was similar to that of the tensile-shear load. When the stress-concentrated joint was homogeneous, it was more robust.

Infrared Small Target Detection Network With Generate Label and Feature Mapping

In the complex background, the contrast and signal-to-noise (SNR) ratio of the infrared (IR) small target are low. Therefore, the traditional IR small target detection algorithms are difficult to achieve good detection performance when the characteristics of small targets are sparse. To solve this problem, an IR small target detection network with generate label and feature mapping (GLFM)-net is proposed in this letter. First, in the GLFM-net model, a scale adaptive feature extraction network is proposed for the IR small target sparse features extraction, and then, the multilayer joint upsampling feature mapping network is proposed for small target feature mapping and background suppression. Based on this model, the feature mapping results of IR dim and small targets with the greatly suppressed background are obtained. Second, in model training, we designed a 2-D Gaussian label generation strategy for the problem of sample imbalance, which can achieve excellent detection performance by using small training samples. The experimental results show that the network can detect IR small targets with different sizes and low SNRs in various complex backgrounds and has good effectiveness and robustness compared with the existing algorithms.

Strength of multilayer metal joints «shaft-sleeve-hub» of rotorcrafts obtained by plastic deformation

Metal multilayer joints are used in the production and repair of transmission parts and control systems of rotorcrafts with intensively wearing surfaces in the form of smooth closed cylindrical and conical holes. The article describes two types of connections: rolled sleeve - hub and shaft - rolled sleeve - hub. The adhesion strength of the joints depends on the frictional forces that prevent the sleeve from displacing relative to the hub. The traction strength is determined by measuring the pressing force and the torque. It depends on the relative tension. An increase in the force of pressing the joint occurs with an increase in the relative tension of mandrel, in proportion to the hardening of the material. The smaller hub wall thickness leads to the more active effect of its springback to the foundation of contact pressure and an increasing of the traction force. Experiments have shown that the forces and moments of traction depend on the angle of the intake cone and the width of the cylindrical tape of the mandrel.

Research on Test and Logging Data Quality Classification for Gas–Water Identification

Tight sandstone oil and gas reservoirs are widely distributed, rich in resources, with a bright prospect for exploration and development in China. Due to multiple evolutions of the structure and sedimentary system, the gas–water distribution laws are complicated in tight sandstone gas reservoirs in the northern Ordos area. It is difficult to identify gas and water layers in the study area. In addition, in the development and production, various factors, such as the failure of the instrument, the difference in construction parameters (injected sand volume, flowback rate), poor test results, and multi-layer joint testing lead to unreliable gas test results. Then, the inaccurate logging responses will be screened by unreliable gas test results for different types of fluids. It is hard to make high-precision fluid logging identification charts or models. Therefore, this article combines gas logging, well logging, testing and other data to research the test and logging data quality classification. Firstly, we select reliable standard samples through the initial gas test results. Secondly, we analyze the four main factors which affect the inaccuracy of gas test results. Thirdly, according to these factors, the flowback rate and the sand volume are determined as the main parameters. Then, we establish a recognition chart of injected sand volume/gas–water ratio. Finally, we proposed an evaluation method for testing quality classification. It provides a test basis for the subsequent identification of gas and water through the second logging interpretation. It also provides a theoretical basis for the exploration and evaluation of tight oil and gas reservoirs.

A Joint Optimization Framework of the Embedding Model and Classifier for Meta-Learning

The aim of meta-learning is to train the machine to learn quickly and accurately. Improving the performance of the meta-learning model is important in solving the problem of small samples and in achieving general artificial intelligence. A meta-learning method based on feature embedding that exhibits good performance on the few-shot problem was previously proposed. In this method, the pretrained deep convolution neural network was used as the embedding model of sample features, and the output of one layer was used as the feature representation of samples. The main limitation of the method is the inability to fuse low-level texture features and high-level semantic features of the embedding model and joint optimization of the embedding model and classifier. Therefore, a multilayer adaptive joint training and optimization method of the embedding model was proposed in the current study. The main characteristics of the current method include using multilayer adaptive hierarchical loss to train the embedding model and using the quantum genetic algorithm to jointly optimize the embedding model and classifier. Validation was performed based on multiple public datasets for meta-learning model testing. The proposed method shows higher accuracy compared with multiple baseline methods.

Design of multi-layered architecture in dissimilar ceramic/metal joints with reinforcements clustering away from both substrates

To combine the advantages of ductile fillers and composite fillers and alleviate residual stress in joints between ZrB2-SiC ceramics (ZS) and TC4-TiBw composites, a novel multi-layered joint architecture composed of a layer of clustering SiC at the center of the joint (L-C-SiC) and two ductile layers without SiC particles bordering both substrates (L-DS) was designed. To achieve this, SiC particle skeletons with continuous micro-channels (SSCC) were integrated with AgCu filler as an interlayer. The effects of SSCC porosity and brazing temperature on joint microstructure and mechanical properties were investigated. In particular, the braze/ZS and braze/SSCC interfaces were analyzed through X-ray diffractometry (XRD), transmission electron microscopy (TEM), and wavelength-dispersive spectroscopy (WDS). The residual stress was also evaluated. The results indicate that increasing the brazing temperate improved the infiltration into the SSCC and promoted the SSCC/braze interface reaction (was detrimental to the SiC particle skeleton). Reducing the SSCC porosity changed the thicknesses of the two L-DSs and enhanced the inhomogeneity of the SSCC/braze interface reaction (induced a shear stress in L-C-SiC). For brazing with an interlayer of 30% porosity at 820 °C, the joint shear strength reached a maximum of ~41.2 MPa, mainly due to the construction of the multi-layered joint architecture.

Prediction method of formation pressure for the adjustment well in the reservoir with fault

Adjustment wells need to be deployed in the middle and late stages of oilfield development to improve development efficiency. However, the multiple pressure systems would be happened in the fault block oilfields due to the geological faults are developed and multi-layer joint water injection. The well kick and leakage would happen during drilling and completion operations of adjustment well because of the large dynamic pressure changes such as high-pressure or low-pressure. A pressure prediction method established base on seepage theory and fluid mechanics theory in order to ensure the safety operations during the adjustment well drilling and completion. This method could predict the maximum formation pressure of adjustment wells in complex fault block reservoirs by considering the influence of faults and surrounding injection-production wells. The error between prediction results and numerical simulation results is less than 10% based on Bohai fault block oilfield. The scheme of shut-in of surrounding water injection wells during drilling and completion of adjustment wells in fault block oilfield is given. This method has significance guidance for the design of shut in adjustment well drilling and completion.

Controllable distribution of reinforcements for reducing the strain energy in dissimilar ceramic/metal joints

A novel design of a multi-layered joint architecture, characterized by the controllable spatial distribution of ceramic reinforcements, was obtained, when brazing ZrB2-SiC ceramics and Ti-6Al-4 V reinforced by TiB whiskers with AgCu filler. To induce SiC reinforcements to cluster together, within the center of the filler and especially away from the ZrB2-SiC, SiC was added into joint, in the form of a SiC interlayer featuring a 3D-bridged network structure with continuous micro-channels infiltrated by capillary force by liquid filler during brazing. Different SiC particles were connected together, by micro-bridges being not destroyed during brazing. The layer rich in SiC could reduce thermal expansion mismatch between different substrates, the AgCu next to the ZrB2-SiC could relax the strain energy by high plastic deformation. Compared to joint brazed with single AgCu, joint strain energy decreased from 10.8 × 10−6 J to 8.6 × 10−6 J, accordingly joint shear strength increased from ∼5.4 MPa to ∼41.2 MPa.

Multilayer Joint Segmentation Using MRF and Graph Cuts

The problem of jointly segmenting objects, according to a set of labels (of cardinality L), from a set of images (of cardinality K) to produce K individual segmentations plus one joint segmentation, can be cast as a Markov random field model. Coupling terms in the considered energy function enforce the consistency between the individual segmentations and the joint segmentation. However, neither optimality on the minimizer (at least for particular cases), nor the sensitivity of the parameters, nor the robustness of this approach against standard ones has been clearly discussed before. This paper focuses on the case where $$L>1$$ , $$K>1$$ and the segmentation problem is handled using graph cuts. Noticeably, some properties of the considered energy function are demonstrated, such as global optimality when $$L=2$$ and $$K>1$$ , the link with majority voting and the link with naive Bayes segmentation. Experiments on synthetic and real images depict superior segmentation performance and better robustness against noisy observations.