Interference Distribution Research Articles

Experimental void fraction measurement approach of small channel two-phase flow

This investigation presents a novel experimental approach for assessing void fraction parameters in two-phase flows within microchannels. The study critiques the conventional impedance methods that utilize alternating current (AC) for void fraction measurements, highlighting the inherent drawbacks such as ground capacitance interference and non-uniform current distribution. To circumvent these issues, the research introduces the use of direct current (DC), which ensures a homogeneous distribution across the conductor's cross-section, as a more reliable alternative. Termed the "Direct Impedance Method," this technique employs DC to enhance the accuracy of void fraction measurements. The study explores various geometric configurations of full-ring and half-ring electrodes, both vertical and horizontal, within a microchannel of 500 μm diameter. An empirical formula is derived to calculate the void fraction from the electrical data obtained. High-speed imaging at 4000 frames per second supplements the method by providing visual confirmation of the flow patterns. The comparative analysis of the direct impedance method and image processing using the homogeneous theoretical model reveals a deviation of approximately 2 %–10 % for the slug and annular flow pattern. In contrast, the deviation is more for the bubble pattern. The results affirm that the Direct Impedance Method is a cost-effective and reasonably precise technique for small-channel applications. Its accuracy is inversely proportional to the channel diameter, rendering it unsuitable for channels larger than 2 mm. The method's low construction cost further enhances its practical appeal.

Application of group decomposition and 1.5-dimensional spectra to acoustic composite fault diagnosis of rolling bearings

Abstract Under the background of strong noise and mutual interference coupling of each fault, the acoustic compound fault diagnosis of rolling bearing is very challenging。 For the composite fault features which are difficult to be extracted due to strong noise interference and uneven distribution of fault intensity, put forward the optimization of swarm decomposition combined with 1.5-dimensional(1.5-d) spectrum method of acoustic composite rolling bearing fault feature separation. The method firstly uses the composite index to iteratively search for the optimal group decomposition threshold value, the adaptive group decomposition of composite fault acoustic signals is realized by optimal parameter group disassembly, and then selects the sensitive components for the decomposed components, and then further analyzes the envelope signal of the sensitive components to reduce the redundancy components and the noise interference, and selects the 1.5-d spectrum to further analyze the envelope signal, thus realizes the effective separation of the composite faults of the rolling bearings acoustic faults. Rolling bearing simulations and experimental acoustic signals verify the validity of the proposed method, and this work gives a new tool for composite fault diagnosis of revolving machinery.

Real-Time Detection and Counting of Wheat Spikes Based on Improved YOLOv10

Wheat is one of the most crucial food crops globally, with its yield directly impacting global food security. The accurate detection and counting of wheat spikes is essential for monitoring wheat growth, predicting yield, and managing fields. However, the current methods face challenges, such as spike size variation, shading, weed interference, and dense distribution. Conventional machine learning approaches have partially addressed these challenges, yet they are hampered by limited detection accuracy, complexities in feature extraction, and poor robustness under complex field conditions. In this paper, we propose an improved YOLOv10 algorithm that significantly enhances the model’s feature extraction and detection capabilities. This is achieved by introducing a bidirectional feature pyramid network (BiFPN), a separated and enhancement attention module (SEAM), and a global context network (GCNet). BiFPN leverages both top-down and bottom-up bidirectional paths to achieve multi-scale feature fusion, improving performance in detecting targets of various scales. SEAM enhances feature representation quality and model performance in complex environments by separately augmenting the attention mechanism for channel and spatial features. GCNet captures long-range dependencies in the image through the global context block, enabling the model to process complex information more accurately. The experimental results demonstrate that our method achieved a precision of 93.69%, a recall of 91.70%, and a mean average precision (mAP) of 95.10% in wheat spike detection, outperforming the benchmark YOLOv10 model by 2.02% in precision, 2.92% in recall, and 1.56% in mAP. Additionally, the coefficient of determination (R2) between the detected and manually counted wheat spikes was 0.96, with a mean absolute error (MAE) of 3.57 and a root-mean-square error (RMSE) of 4.09, indicating strong correlation and high accuracy. The improved YOLOv10 algorithm effectively solves the difficult problem of wheat spike detection under complex field conditions, providing strong support for agricultural production and research.

Associations between smoking history, baseline pain interference and symptom distribution, and physical function at discharge, in individuals seeking care for musculoskeletal pain

ObjectiveStudy of the association between smoking and pain intensity has produced conflicting results; with less focus on pain interference. Different pain constructs could have varying associations with smoking behaviors. This study sought to investigate the association between smoking history and not only pain intensity, but also pain interference, symptom distribution and physical function. MethodsSmoking history (current, past, or none), pain interference (Pain, Enjoyment of Life, and General Activity scale), symptom distribution and physical function scores were extracted from medical records of patients seen in physical therapy for common sites of musculoskeletal pain (lumbar and cervical spine, knee, or hip). Generalized linear models assessed the relationship between smoking history and pain/function. Results833 patients from an integrated healthcare system were included (mean: 57.6 years, SD=16.3; 43 % male). After controlling for several variables, current smokers had significantly higher baseline pain interference scores compared to never and former smokers (beta [B]: 0.65, 95 %CI: 0.13 to 1.18, P=.02). Smoking was not a significant predictor of symptom distribution at baseline [B: 0.17, 95 %CI −0.06 to 0.42, P=.16] or physical function scores at discharge [B: -0.03, 95 %CI: −0.08 to 0.02, P=.25]. ConclusionSmokers experienced a greater impact of pain at baseline. However, symptom distribution at intake and function upon discharge were similar between all smoking groups. These findings suggest smoking cessation and abstinence may be important recommendations to help curb pain interference.

Analytical method for contact characteristics of rubber shaft seals under dynamic eccentricity considering viscous effect

This study introduces a methodology for analyzing the viscous effect on rubber shaft seals under dynamic eccentricity. It models the radial motion of the shaft seal and quantifies the viscous force arising from the viscous effect. A 3-D FEM with a noncircular shaft is established, equating viscous force to the interference distribution equation. Then, simulated mounting yield contact characteristics. Findings indicate increased interference with the viscous effect and heightened sensitivity of contact characteristics to eccentricity and rotational speed variations. This approach enhances precision in calculating rubber shaft seal contact characteristics under dynamic eccentricity.

Double parton distributions with flavor interference from lattice QCD

We study double parton distributions with flavor interference in the nucleon and compare them with previous results for the flavor diagonal case. We investigate both unpolarized and polarized partons. We compare our lattice results with those obtained from the simple description of the proton in terms of an SU(6) symmetric three-quark wave function and find that this description fails for both flavor and polarization dependence. We also derive and test a factorization ansatz for the unpolarized flavor interference distribution in terms of single-parton distributions and find that this ansatz fails to a large extent.

Алгоритми цифрової обробки кореляційних функцій у течешукачах

The article is devoted to the processing of cross-correlation functions. The need for this processing is due to a wide variety of interference conditions for searching for leaks in underground pipelines. Interference often significantly distorts the appearance of correlation functions and makes it difficult to accurately determine the coordinates of damage for pipeline repairs. Various approaches to combating these distortions are considered, depending on the available information about the characteristics of interference and leakage noise. Such features as the characteristic delay of the correlation function, which often corresponds to an interference burst and features of the frequency distributions of interference and leakage noise. An algorithm for extracting the leak coordinate from the correlation function as the coordinate of the source of a broadband signal by orthogonal decomposition of the CCF is considered. This problem is solved on the basis of classical approaches to the synthesis of shaping and synthesis of matched filters. The connection between the results obtained is shown. Thus, two approaches were used: one has the main goal of suppressing interference, without directly determining the coordinates of leaks, the other, on the contrary, is focused primarily on the selection of useful correlation of leak noises. In real-life conditions, it is advisable to combine both approaches due to the variety of acoustic environments encountered.

Test-Time Domain Adaptation by Learning Domain-Aware Batch Normalization

Test-time domain adaptation aims to adapt the model trained on source domains to unseen target domains using a few unlabeled images. Emerging research has shown that the label and domain information is separately embedded in the weight matrix and batch normalization (BN) layer. Previous works normally update the whole network naively without explicitly decoupling the knowledge between label and domain. As a result, it leads to knowledge interference and defective distribution adaptation. In this work, we propose to reduce such learning interference and elevate the domain knowledge learning by only manipulating the BN layer. However, the normalization step in BN is intrinsically unstable when the statistics are re-estimated from a few samples. We find that ambiguities can be greatly reduced when only updating the two affine parameters in BN while keeping the source domain statistics. To further enhance the domain knowledge extraction from unlabeled data, we construct an auxiliary branch with label-independent self-supervised learning (SSL) to provide supervision. Moreover, we propose a bi-level optimization based on meta-learning to enforce the alignment of two learning objectives of auxiliary and main branches. The goal is to use the auxiliary branch to adapt the domain and benefit main task for subsequent inference. Our method keeps the same computational cost at inference as the auxiliary branch can be thoroughly discarded after adaptation. Extensive experiments show that our method outperforms the prior works on five WILDS real-world domain shift datasets. Our method can also be integrated with methods with label-dependent optimization to further push the performance boundary. Our code is available at https://github.com/ynanwu/MABN.

FILTERING OF AN INTERRUPTED SIGNAL ON APPROXIMATION BY GAMMA DISTRIBUTION UNDER THE INFLUENCE OF ADDITIVE MULTIPLICATIVE INTERFERENCE

The problem of constructing an algorithm for recognizing and filtering a continuous-valued Markov process measured in a mixture with random additive and multiplicative interference under conditions of random information interruptions is considered. The Bayes principle and the well-known two-stage filtering method “forecast-correction” are applied, supplemented by procedures for identifying the number of the structure, in which the system is located in the current and next time intervals. At the forecast stage, identification is based on calculating the probabilities of the future state of the system based on a priori information about the probabilities of its transitions from structure to structure, as well as on the current values of estimates of these probabilities. At the correction stage, identification is based on the use of probability prediction results and a priori known information about the reliability of the information of the system status indicator. In addition, the values of the probability densities of the measuring information in each structure are used, the expressions for which are obtained on the basis of a priori known laws of distribution of additive and multiplicative interference, as well as the predicted probability density of the Markov process in each structure at the next step of calculations. To obtain a practically realizable algorithm, expressions for the predicted and a posteriori densities of the Markov process probabilities are obtained based on their approximation by the probability density of the gamma distribution, completely determined by the first two initial moments. This made it possible to obtain a closed system of recurrent equations for estimating the probability of information interruption, mathematical expectations and variances of the Markov process in each structure.

Research on optimization technology of excitation coil in downhole annular flow electromagnetic measurement system

External interference and non-uniform velocity distribution influence the downhole annular flow electromagnetic measurement, reducing detection accuracy. Optimizing the structure of the excitation coil can effectively enhance the uniformity of magnetic field distribution, constituting an essential approach for improving measurement accuracy. Aiming at the excitation coil optimization technology of annular flow electromagnetic measurement system, the study first analyzes and obtains the magnetic field model of the excitation coil based on the principle of annular flow electromagnetic measurement, combined with the theory of vector weight function and puts forward the optimization theory of annular excitation coil. Secondly, the simulation models of rectangular and saddle exciting coils are established using finite element software to analyze the magnetic field distribution of annular flow under different coil and core sizes. The optimal structural parameters of the exciting coils in the annular flow electromagnetic measurement system are determined through evaluation indexes for the magnetic field. Finally, an experimental platform was established for optimizing the electromagnetic measurement of annular flow, and this platform was used to conduct comparative experiments. The experimental results show that the maximum reduction of the optimized system is 3.192%, 1.289%, and 1.813% for the single verification relative value error, single-point verification relative value error, and repeatability compared with the rectangular excitation coil annular flow electromagnetic measurement system. In the flow measurement interval of 25–100 m3 h−1, the single-point verification of the optimized system has a maximum relative display value error of 0.378%, and the measurement accuracy reaches 1.0 level and meets the consistency of the transmission of quantity and value. The research findings hold significant guidance for enhancing the measurement accuracy of the downhole annular flow electromagnetic measurement system.

Promoting the uniform propagation of multi-fracture through adjusting the injection rate and perforation parameter: A numerical study

The strong stress interference and fluid competitive distribution result in the non-uniform propagation of multiple fractures during horizontal well multi-stage hydraulic fracturing (HWMHF). The uniform stimulation effect can be effectively improved by adjusting the injection rate and perforation scheme. In this work, a two-dimensional fluid–solid fully coupled multi-fracture propagation model is established to investigate the pattern of multi-fracture propagation and the flow distribution. The considering factors include the fluid injection rate, the perforation parameters, and the reservoir heterogeneity. The pipe element is developed to realize the free fluid distribution among multiple fractures. The results show that multiple fractures are more likely to initiate simultaneously and propagate uniformly with a higher fluid injection rate. The stress interference among multiple fractures can be balanced and the equilibrium propagation degree of multiple fractures can be greatly improved by reducing the perforation number. In the homogeneous reservoir, when the fluid injection rate is 12 m3/min and the perforation number per cluster is reduced to 10, the difference coefficient of fluid distribution can be reduced to 3.31%. In the heterogeneous reservoir, multiple perforation clusters with different tensile strengths can generate nearly uniform fractures by increasing the fluid injection rate and reducing the perforation number. When the fluid injection rate is 12 m3/min and the perforation number per cluster is 6, the difference coefficient of fluid distribution can be reduced to 3.26%. This work is of great significance in clarifying the propagation pattern and optimizing the fluid injection rate and the perforation number to improve the uniform propagation degree of multiple fractures.

Study on the influence of the transmission tower on the AC interference distribution on the surface of a buried steel pipeline under steady-state conditions

Study on the influence of the transmission tower on the AC interference distribution on the surface of a buried steel pipeline under steady-state conditions

Impact of well interference on transient pressure behavior during underground gas storage: A comparative study

Underground natural gas storage (UGS) serves as an environmentally sustainable remedy for mitigating regional and temporal disparities in energy supply and demand. The phenomenon of substantial well interference and non-uniform pressure distributions in UGS, resulting from high injection and withdrawal rates, requires a comprehensive examination. This study presents an analytical model aimed at investigating the ramifications of well interference on transient pressure dynamics during UGS. Employing the Laplace transform method, an analytical framework for diverse wells within UGS is derived, with well interference effects being effectively incorporated through the application of the superposition principle. To validate the proposed analytical solutions under various scenarios, a commercial numerical simulator is employed. The analysis reveals that when an adjacent well is engaged in gas withdrawal, interference induces an initial rise in pressure derivative followed by a subsequent plateau. Conversely, during gas injection into an adjacent well, the pressure derivative curve exhibits a continuous decline, akin to situations characterized by constant pressure boundaries. Notably, the likelihood of interference with a target well is more pronounced when gas injection or production occurs in a vertical well as opposed to a horizontal one. Preliminary data from the Hutubi UGS in China, one of the largest projects of its kind, indicate cumulative gas injection and withdrawal volumes of 155.43 × 108 m3 and 130.81 × 108 m3, respectively, with a maximum storage capacity of 107 × 108 m3. Ultimately, the gas storage volume reaches 93.50% of the UGS's designated capacity. This substantial quantity of stored natural gas equates to the calorific value of 9.88 × 109 kg of crude oil or 1.29 × 1010 kg of coal. In comparison to conventional fossil fuels such as oil and coal, the utilization of natural gas in the Hutubi UGS results in a significant reduction of carbon dioxide emissions, amounting to 1.04 × 1010 kg and 1.38 × 1010 kg, respectively. This contribution advances the field by proposing an analytical model for the systematic analysis of well interference on pressure dynamics within the Hutubi UGS, thereby facilitating the transition from oil and coal to natural gas, a crucial step in the pursuit of cleaner and more sustainable energy production practises.

Orthogonal Circulant Multiplexing for Bandwidth- Limited Direct-Detected Optical Communication Systems

We propose and investigate a novel orthogonal circulant multiplexing (OCM) technology for bandwidth-limited direct detection (DD) optical systems. We analytically derive that any OCM, i.e. using any orthogonal circulant matrix for multiplexing, can redistribute the noise uniformly across the subcarriers. However, the distribution of inter-symbol interference (ISI) and inter-carrier interference (ICI) strongly depends on the design of OCM. The previously proposed orthogonal chirp division multiplexing (OCDM), although showing better ISI/ICI tolerance than discrete-Fourier-transform spread (DFT-S) orthogonal frequency division multiplexing (OFDM), is a kind of OCM with poorer performance. We propose and analytically reveal that OCM based on chirp-like polyphase sequence (CLPS), general chirp sequence (GCS), sparse CLPS (SCLPS), and sparse GCS (SGCS) can achieve flatter ISI/ICI distribution across subcarriers and so better performance than OCDM in bandwidth-limited DD systems. The optimal parameter vector of the E-parameter CLPS is a Zadoff-Chu sequence while the parameter α in GCS should be larger. The optimal performance can be achieved by either CLPS (or GCS) using a larger E (or α) or SCLPS (or SGCS) with optimized sparsity. ∼110Gbit/s experiments using Mach-Zehnder modulator or electro-absorption modulator and receiver of 10-GHz photodiode or 8-GHz avalanche photodiode are conducted. The results agree with the theory and show that the proposed OCM outperforms conventional OFDM, DFT-S OFDM, and OCDM.

Analysis of TB2 rivet forming quality and mechanical properties of thin sheet riveted joints based on different riveting methods

The riveting of high-strength rivets (such as TB2 (Ti-5Mo-5V-8Cr-3Al)) faces difficulties in forming. This article compares the electromagnetic riveting (EMR) and the hot riveting (HR) joints of two typical TB2 rivets (the flat cone head rivet and the countersunk head rivet). The interference and hardness distributions of the rivets were measured, and the strength of the joints was tested. Moreover, the microstructures of rivets after riveting and the fractured surfaces after the shear and pull-out tests were both observed. The results indicate that the interference of the EMR joints is greater and more uniform than that of the HR joints. The deformation of the EMR driven head is more severe than that of the HR. Higher hardness is measured in the driven head and the rivet shank at the positions of severe deformation. The hardness of the EMR driven head and rivet shank is higher than that of the HR. Additionally, it will not cause a decrease and even slightly improve in the mechanical properties of the joint when using the EMR riveting TB2. The pull-out strength of flat cone head rivet joints is significantly higher than that of countersunk rivet joints due to the influence of the structure strength of the manufactured head. The fracture mode of all joints is mixed fracture. However, the failure mode of joint varies greatly due to the influence of rivet structure and riveting method. When using the EMR instead of the HR to rivet the TB2 rivets, it will not cause a decrease in the mechanical properties of the joint. Therefore, it is indicated that the EMR can be used to replace the HR.

Targeting Filamenting temperature-sensitive mutant Z (FtsZ) with bioactive phytoconstituents: An emerging strategy for antibacterial therapy.

The rise and widespread occurrence of bacterial resistance has created an evident need for novel antibacterial drugs. Filamenting temperature-sensitive mutant Z (FtsZ) is a crucial bacterial protein that forms a ring-like structure known as the Z-ring, playing a significant role in cell division. Targeting FtsZ is an effective approach for developing antibiotics that disrupt bacterial cell division and halt growth. This study aimed to use a virtual screening approach to search for bioactive phytoconstituents with the potential to inhibit FtsZ. The screening process proceeded with the filtering compounds from the IMPPAT library of phytochemicals based on their physicochemical properties using the Lipinski rule of five. This was followed by molecular docking, Pan-assay interference compounds (PAINS) filter, absorption, distribution, metabolism, excretion, and toxicity (ADMET), prediction of activity spectra for biologically active substances (PASS), and molecular dynamics (MD) simulations. These filters ensured that any adverse effects that could impede the identification of potential inhibitors of FtsZ were eliminated. Following this, two phytocompounds, Withaperuvin C and Trifolirhizin, were selected after the screening, demonstrating noteworthy binding potential with FtsZ's GTP binding pocket, acting as potent GTP-competitive inhibitors of FtsZ. The study suggested that these compounds could be further investigated for developing a novel class of antibiotics after required studies.

Inner-cavity generation of mid-infrared optical vortex arrays from an Er:CaF2 laser

We demonstrate the inner-cavity generation of mid-infrared optical vortex arrays from an Er:CaF2 laser. By shifting the position of the defect point on the input mirror, multiple transverse modes simultaneously oscillated in the cavity and constituted vortex arrays by transverse mode locking. The maximum output power of TEM00 mode could reach 440 mW with a low threshold of 463 mW. The maximum output powers of LG0,1, the 1 × 2 and the 2 × 2 vortex arrays were 254 mW, 131 mW, and 117 mW, respectively. The chirality of the vortex arrays could be reversed by slightly adjusting the geometric loss of the cavity. The light intensity distribution, interference, and phase distribution were simulated and they were in good accordance with the experimental results. This method provides deep insight into inner-cavity generation of vortex arrays in mid-infrared regime.

Interference Analysis for UAV Radar Networks With Guard Zones Based on Stochastic Geometry

Due to the increasing number of aerial radars and joint communication/sensing technologies, interference from uncoordinated radars will limit the target detection and ranging performance in the future. In this paper, we investigate the interference behavior in an aerial radar network for sensing ground targets. We consider that the radars mounted on unmanned aerial vehicles (UAVs) that fly at a certain altitude are randomly distributed according to a two-dimensional homogeneous Poisson point process (HPPP), and that the propagation is modeled using a probabilistic line-of-sight (LoS) channel model. For such a sensing network, we derive the distribution of the radar interference using a stochastic geometry based analysis. In particular, when Swerling I model is considered for radar cross-section area (RCS) for the target, we derive the Laplace transform of the radar interference. To avoid a strong interference between neighboring radars, a guard zone is introduced within which the UAV radar transmission around the permitted active radar is inhibited. As the radar performance metric, we derive the successful ranging probability (SRP) of a given radar by exploiting the Laplace transform of radar interference. Using the analytic SRP, we show that we can optimize the radar network parameters such as the radius of the guard zone and the density of the active radars. In addition, we also discuss how the analytic SRP gives an insight into the spectrum utilization strategy for the UAV radar networks with the guard zones.

Double-Slit Interference in the Ion Dynamics of Dissociative Photoionization.

The ion momentum distribution in the x-ray-induced dissociative photoionization of molecules is investigated, treating the ionization analytically under the Born-Oppenheimer approximation and simulating numerically the ion motion via the Schrödinger equation. The ion-photoelectron entanglement transfers information of the electronic interference to the ion dynamics. As a consequence, the ion momentum distributions of dissociative molecular photoionization present Young's double-slit interference when the photoelectron emission angle is fixed. We demonstrate that double-slit interference signatures persist in the ion longitudinal momentum shift even when the information of the correlated photoelectron is lost, which is the case for heteronuclear molecules when an additional photoelectron recoil momentum arises due to the different ion masses. For the case of sequential double ionization, we show that double-slit interference in the ion dynamics can be utilized for coherent control of the molecular dynamics.

Self-Interference Suppression of Unmanned Underwater Vehicle with Vector Hydrophone Array Based on an Improved Autoencoder

The self-interference of an unmanned underwater vehicle (UUV) weakens its ability to detect targets of interest. Due to limitations in the size of the sonar array and the complexity of the interference, the performance of existing self-interference suppression methods in practical applications is unsatisfactory. Our research focuses on analyzing the influence of near-field interferences on the sample covariance matrix (SCM) and proposes an interference suppression algorithm based on an improved autoencoder. The proposed algorithm effectively learns the feature distribution of near-field interferences within the covariance domain and reconstructs the pure signal covariance matrix through the cancellation of the near-field interference features. Moreover, the proposed algorithm can meet the requirements of real-time processing and does not require prior knowledge about the positions or propagation of interference. Simulations demonstrate that the proposed algorithm outperforms comparison methods, particularly in scenarios with low signal-to-interference ratios and a limited number of sensors. Furthermore, lake experiments provide additional evidence of the proposed algorithm’s good performance in practical applications.