Two-dimensional Plane Research Articles

Taguchi Method-Based Synthesis of a Circular Antenna Array for Enhanced IoT Applications

Linear antenna arrays exhibit radiation patterns that are restricted to a half-space and feature axial radiation, which can be a significant drawback for applications that require omnidirectional coverage. To address this limitation, the synthesis method utilizing the Taguchi approach, originally designed for linear arrays, can be effectively extended to two-dimensional or planar antenna arrays. In the context of a linear array, the synthesis process primarily involves determining the feeding law and/or the spatial distribution of the elements along a single axis. Conversely, for a planar array, the synthesis becomes more complex, as it requires the identification of the complex weighting of the feed and/or the spatial distribution of sources across a two-dimensional plane. This adaptation to planar arrays is facilitated by substituting the direction θ with the pair of directions (θ,ϕ), allowing for a more comprehensive coverage of the angular domain. This article focuses on exploring various configurations of planar arrays, aiming to enhance their performance. The primary objective of these configurations is often to minimize the levels of secondary lobes and/or array lobes while enabling a full sweep of the angular space. Secondary lobes can significantly impede system performance, particularly in multibeam applications, where they restrict the minimum distance for frequency channel reuse. This restriction is critical, as it affects the overall efficiency and effectiveness of communication systems that rely on precise beamforming and frequency allocation. By investigating alternative planar array designs and their synthesis methods, this research seeks to provide solutions that improve coverage, reduce interference from secondary lobes, and ultimately enhance the functionality of antennas in diverse applications, including telecommunications, radar systems, and wireless communication.

Collective motion of energy depot active disks.

In the present work we have studied collectives of active disks with an energy depot, moving in the two-dimensional plane and interacting via an excluded volume. The energy depot accounts for the extraction of energy taking place at the level of each particle in order to perform self-propulsion, included in an underdamped Langevin dynamics. We show that this model undergoes a flocking transition, exhibiting some of the key features of the Vicsek model, namely, band formation and giant number fluctuations. These bands, either single or multiple, are dense and very strongly polarised propagating structures. Large density bands disappear as the activity is further increased, eventually reaching a homogeneous polar state. We unravel an effective alignment interaction at the level of two-particle collisions that can be controlled by activity and gives rise to flocking at large scales.

Diffraction managed modulation instability of two-dimensional plane wave in competing cubic-quintic nonlinear media

Diffraction managed modulation instability of two-dimensional plane wave in competing cubic-quintic nonlinear media

VARIATIONAL-DIFFERENCE SOLUTION OF DEFORMATION AND BUCKLING PROBLEMS OF ELASTOPLASTIC SHELLS OF REVOLUTION WITH ELASTIC FILLER UNDER COMBINED QUASI-STATIC AND DYNAMIC AXISYMMETRIC LOADINGS

The paper suggests a formulation and method for a numerical solution of deformation and buckling of elastoplastic shells of revolution with elastic filler under quasi-static and dynamic loadings. The problem is solved in a two-dimensional plane or generalized axisymmetric formulation with torsion. The governing system of equations is written in a Cartesian or cylindrical coordinate system. Modeling of deformation of an elastic-plastic shell is carried out based on the hypotheses of the theory of shells of the Timoshenko type, taking into account geometric nonlinearities. Kinematic relations are written in velocities and formulated in the metric of the current state. The elastoplastic properties of the shell are described by the flow theory with nonlinear isotropic hardening. Filler modeling is based on continuum mechanics hypotheses. The filler material is assumed to be linearly elastic. The variational equations of motion of structural elements (both shells and filler) are reduced from the three-dimensional equation of the balance of virtual powers of the work of continuum mechanics taking into account the accepted hypotheses of the theory of shells or a flat deformed state or generalized axisymmetric deformation with torsion. The modeling of the contact interaction between the shell and the filler is based on the condition of nonpenetration along the normal and slippage along the tangential. The finite-difference method and an explicit time integration scheme of the cross type are used to solve the defining system of equations. Approbation of the technique was carried out on the problem of buckling of a steel cylindrical shell with an elastic filler under quasi-static and dynamic compression by an external pressure that linearly increases with time. The results of the numerical study are compared with calculations performed using two other approaches developed earlier by the authors. The first approach is based on full-scale modeling of the process of deformation of the shell and filler within the framework of continuum mechanics. In the second approach, a simplified formulation is used, in which the deformation of the shell is modeled according to the hypotheses of the theory of non-sloping shells of the Timoshenko type taking into account geometric nonlinearities, and the filler is modeled according to the Winkler foundation hypothesis. The developed approaches make it possible to model the nonlinear subcritical deformation of shells of revolution with an elastic filler, to determine the ultimate (critical) loads in a wide range of loading rates taking into account geometric shape imperfections, to study buckling in axisymmetric and non-axisymmetric shapes under dynamic and quasi-static combined loadings in plane and axisymmetric deformations.

A Study on the Application of a Deep Thermal Reservoir by Using a Magnetotelluric Sounding Method: Taking an Example of Geothermal Resources’ Exploration in the Western Taikang Uplift of the Southern North China Basin

Geothermal resources are abundant in the Southern North China Basin, which is one of the prospective areas hosting low–medium-temperature geothermal resources in sedimentary basins in China. The purpose of this work is to reveal the formation and storage conditions of the geothermal resources in the western margin of the Taikang Uplift and delineate the range of potential geothermal reservoirs. This paper uses five magnetotelluric sounding profiles for data processing and analysis, including the calculation of 2D skewness and electric strike. Data processing, analysis, and NLCG 2D inversion were performed on MT data, which consisted of 111 measurement points, and reliable two-dimensional resistivity models and resistivity planes were obtained. In combination with drilling verification and the analysis of geophysical logging data, the stratigraphic lithology and the range of potential geothermal reservoirs were largely clarified. The results show that using the magnetotelluric sounding method can well delineate the range of deep geothermal reservoirs in sedimentary basins and that the MT method is suitable for exploring buried geothermal resources in deep plains. The analytical results showed that the XZR-1 well yielded 1480 cubic meters of water per day, with the water temperature of the wellhead being approximately 78 °C, and combined with the results of this electromagnetic and drilling exploration, a geothermal geological model and genesis process of the west of the Taikang Uplift area was constructed. The water yield and temperature were higher than those of previous exploration results, which has important guiding significance for the future development and utilization of karst fissure heat reservoirs in the western Taikang Uplift.

Two-dimensionally stable self-organisation arises in simple schooling swimmers through hydrodynamic interactions

We present new constrained and free-swimming experiments and simulations in the inertial regime, with Reynolds number $\mbox{Re} = O(10^4)$ , of a pair of two-dimensional and three-dimensional pitching hydrofoils interacting in a minimal school. The hydrofoils have an out-of-phase synchronisation, and they are varied through in-line, staggered and side-by-side formations within the two-dimensional interaction plane. It is discovered that there is a two-dimensionally stable equilibrium point for a side-by-side formation. This formation is super-stable, meaning that hydrodynamic forces will passively maintain this formation even under external perturbations, and the school as a whole has no net forces acting on it that cause it to drift to one side or the other. Previously discovered one-dimensionally stable equilibria driven by wake vortex interactions are shown to be, in fact, two-dimensionally unstable, at least for an out-of-phase synchronisation. Additionally, it is discovered that a trailing-edge vortex mechanism provides the restorative force to stabilise a side-by-side formation. The stable equilibrium is further verified by experiments and simulations for freely swimming foils where dynamic recoil motions are present. When constrained, swimmers in compact side-by-side formations experience collective efficiency and thrust increases up to 40 % and 100 %, respectively, whereas slightly staggered formations output an even higher efficiency improvement of 84 %, with an 87 % increase in thrust. Freely swimming foils in a stable side-by-side formation show efficiency and speed enhancements of up to 9 % and 15 %, respectively. These newfound schooling performance and stability characteristics suggest that fluid-mediated equilibria may play a role in the control strategies of schooling fish and fish-inspired robots.

Visual Analysis of Anomalous Behavior Patterns in Oil Wells Using Dimensionality Reduction with t-SNE Projection

Anomaly detection in production processes, especially in the oil industry, is of paramount importance due to the complexity and criticality of these systems. Producing oil wells are subject to a series of dynamic and interdependent variables, which can be monitored using sensors installed along the well. Precise analysis of these sensor records is essential for early identification of possible anomalies, as any deviation from the normal pattern can result in serious consequences, from operational failures to environmental and safety risks. Given the multidimensionality and variability of this data, the use of machine learning techniques becomes indispensable for analyzing and classifying the well's situation. However, even for computational software, anomaly identification remains a significant challenge, given the oscillatory behavior and scale disparity of the variables analyzed throughout the well's productive life. To mitigate these challenges, dimensional reduction techniques can be implemented, as they can bring some advantages, such as reducing computational cost, noise reduction, and improving classifier accuracy. A widely used tool for dimensional reduction, especially for visualization, is Distributed Stochastic Neighbor Embedding (t-SNE), which seeks to project high-dimensional data into a low-dimensional space preserving clusters, bringing similar data together by affinity through a t-distribution. For this approach, real records of pressure and temperature sensors from oil wells are used. These sensors are located at eight distinct points in the well, totaling eight dimensions that will be reduced to a two-dimensional plane. Therefore, this study aims to identify behavior patterns in multivariate data from producing oil wells visually using the t-SNE dimensionality reduction method. It is expected that through visualization, it will be possible to identify behavior patterns before and after the occurrence of anomalies and enable the development of appropriate artificial intelligence algorithms for this anomaly detection problem.

NETWORK INTRUSION DETECTION MODEL BASED ON CONVOLUTIONAL NEURAL NETWORKS AND TABULAR DATA CONVERTED INTO IMAGES

The object of the study is the process of identifying the state of a computer systems and network. The subject of the study are the methods of identifying the state of computer systems and networks. The purpose of this paper is to improve the quality of detecting intrusions into computer networks. The UNSW-NB 15 set, which contains information about the normal functioning of the network and during synthetic intrusions, was used as input. Deep neural networks (DL), their advantages and problems in big data processing are considered. It was found that deep neural networks when processing tabular data require their transformation. Modern methods of tabular data transformation were studied. The results obtained. A method of converting tabular data into an image is proposed. The method converts each object of a separate class from a set of tabular data into an image by mapping the attribute values onto a two-dimensional plane. The method was implemented programmatically using the GOOGLE COLAB cloud service based on Jupyter Notebook. Conclusions. It was found that the use of the proposed conversion method of tabular data into an image made it possible to use a classification model based on the CNN neural network and increase the quality of detection of intrusions into computer networks up to 4%.

Tower Crane Layout Planning: Multi-Optimal Solutions Algorithm

Effective tower crane layout planning is essential for the success of construction projects. Traditional optimization algorithms, which often provide a single optimal solution, may not always reveal the global optimum, leaving room for doubt. This paper introduces the competitor algorithm, a novel multi-optimal solution approach inspired by the competitive learning paradigm within classroom settings. This algorithm is designed to provide users with a diverse set of competitive solutions, while avoiding falling into local optima. This strategic diversification ensures that users are equipped with a comprehensive range of options, empowering them to make confident, informed decisions. Furthermore, we have streamlined the positioning range for tower cranes, transitioning from a two-dimensional plane to a one-dimensional segmented line, thus eliminating the need to explore extensive, non-competitive regions. The competitor algorithm’s performance was validated through practical application, showcasing both its stability and optimization prowess, thereby confirming its reliable utility in real-world scenarios.

Research on intelligent three-dimensional anchor position detection method for ships utilizing Traversal and Monte Carlo algorithms

As intelligent ship technology advances, the importance of intelligent anchor position detection, as one of the key technologies, can ensure the safe anchoring of ships and enhance the efficiency of port operation. At present, most of the anchor position selection and detection algorithms are mainly based on two-dimensional planes, and there is a lack of research on the intelligent detection of safe water depth for ship anchoring in three-dimensional space. It not only restricts the full utilization of anchorage resources but also affects the safety and environmental adaptability of anchoring operations. To address these issues, this study proposes a three-dimension anchor position detection method. Firstly, based on the establishment of a three-dimensional ocean model, the possible anchor positions selected by the ship are simulated using the Monte Carlo algorithm. Secondly, the simulated anchor positions are optimized using a Traversal algorithm to filter out the optimal anchoring position that meets the requirements, the safety distance between each point and the existing ship is calculated, and the anchor position is determined according to the corresponding required safety spacing. Finally, to verify the applicability and effectiveness of the method under different sea conditions and different ship types, this study conducts a series of simulation experiments with 5000 random samples. These experiments compare the demand of anchor position selection for anchoring ships with changing water depths in the case of empty and full load drafts, and visualize the impact of varying water depth parameters on the selection of anchor positions for anchoring ships in various ship types. The outcomes of the experiment indicate that the algorithm’s detection area encompasses the whole anchorage area, ensuring both the anchorage area’s usage rate and the accuracy of anchor position detection. This study demonstrates that the Traversal and Monte Carlo Algorithms effectively improve the accuracy of the selection of anchoring position of the ship, makes full use of the resources of anchorage, and further improves the safety and efficiency of the anchoring operation.

Numerical simulation study on the construction of cut off walls using high-pressure jet grouting based on SPH method

The optimization of parameters for the construction of cut off walls using high spray method plays a crucial role in improving the permeability stability of hydraulic structures and ensuring the safe operation of water conservancy projects. However, limited by existing research methods, there is currently a lack of systematic research on the influence of construction parameters on the quality of cut off walls. This study fully considers the characteristics of high-speed slurry jet and soil dynamic failure in numerical simulation of the construction of cut off walls using high spray method. Based on the SPH method, a two-dimensional plane strain model of high-pressure jet grouting was established, and the influence of aperture, grouting pressure, and hole spacing on the failure process of soil and the quality of cut off walls is systematically analyzed. The results show that the soil mainly exhibits tensile failure under the continuous action of high-speed cement slurry during the construction of cut off walls using high spray method. Reducing the aperture and grouting pressure, as well as increasing the hole spacing, are not conducive to forming a continuous and dense impermeable wall. Compared to grouting pressure, the influence of aperture and spacing on the quality of cut off walls is more significant. When the aperture is 0.6 m, the grouting pressure is 32 MPa, and the hole spacing is 0.8 m, the quality of cut off walls is great. Finally, the simulation results of this paper were preliminarily verified by combining the construction of cut off walls using high spray method in the flood control project in Luotang Township, Jiangxi Province, China. The findings can provide reference for optimizing the construction parameters of cut off walls using high spray method.

Performance analysis of various wall treatments of RANS models for prediction of near-wall turbulence transport characteristics of plane wall jet

PurposeThe present study scrutinizes the relative performance of various near-wall treatments coupled with two-equation RANS models to explore the turbulence transport mechanism in terms of the kinetic energy budget in a plane wall jet and the significance of the near-wall molecular and turbulent shear, to select the best combination among the models which reveals wall jet characteristics most efficiently.Design/methodology/approachA two-dimensional steady incompressible plane wall jet in a quiescent surrounding is simulated using ANSYS-Fluent solver. Three near-wall treatments, namely the Standard Wall Function (SWF), Enhanced Wall Treatment (EWT) and Menter-Lechner (ML) treatment coupled with Realisable, RNG and Standard k-e models and also the Standard and Shear-Stress Transport (SST) k-ω models are employed for this investigation.FindingsThe ML treatment slightly overestimated the budget components on an outer scale, whereas the k-ω models strikingly underestimated them. In the buffer layer at the inner scale, the SWF highly over-predicts turbulent production and dissipation and k-ω models over-predict dissipation. Appreciably accurate inner and outer scale k-budgets are observed with the EWT schemes. With a sufficiently resolved near-wall mesh, the Realisable model with EWT exhibits the mean flow, turbulence characteristics and turbulence energy transport even better than the SST k-ω model.Originality/valueThree distinct near-wall strategies are chosen for comparative performance analysis, focusing not only on the mean flow and turbulence characteristics but the turbulence energy budget as well, for finding the best combination, having potential as a viable and low-cost alternative to LES and DNS for wall jet simulation in industrial application.

Acoustofluidic tweezers via ring resonance.

Ring resonator (RR) devices are closed-loop waveguides where waves circulate only at the resonant frequencies. They have been used in sensor technology and optical tweezers, but controlling micron-scale particles with optical RR tweezers is challenging due to insufficient force, short working distances, and photodamage. To overcome these obstacles, an acoustofluidic RR-based tweezing method is developed to manipulate micro-sized particles that can enhance particle trapping through the resonance interaction of acoustic waves with high Q factor (>3000), more than 20 times greater than traditional acoustic transducers. Particles can be precisely manipulated within the RR by adjusting the signal phase, with trapping amplified by enlarging the connected waveguide. Rapid particle mixing is achieved when particles are placed between the waveguide and RR. The signal path is strengthened by strategically positioning the RR in a two-dimensional plane. Acoustofluidic RR tweezers have immense potential for advancing applications in biosensing, mechanobiology, lab-on-a-chip, and cell-cell communication research.

Sub-Micron Two-Dimensional Displacement Sensor Based on a Multi-Core Fiber

A sub-micron two-dimensional displacement sensor based on a segment of multi-core fiber is presented in this paper. Light at the wavelengths of 1520 nm, 1530 nm, and 1540 nm was introduced separately into three cores of a seven-core fiber (SCF). They were independently transmitted in their respective cores, and after being emitted from the other end of the SCF, they were irradiated onto the end-face of a single-mode fiber (SMF). The SMF received light at three different wavelengths, the power of which was related to the relative position between the SCF and the SMF. When the SMF moved within a two-dimensional plane, the direction of displacement could be determined based on the changes in power at different wavelengths. As a benefit of the high sensitivity of the spectrometer, the sensor could detect displacements at the sub-micron level. When the SMF was translated in 200 nm steps over a range from 5.2 μm to 6.2 μm, the sensitivities at the wavelengths of 1520 nm, 1530 nm, and 1540 nm were 0.34 dB/μm, 0.40 dB/μm, and 0.36 dB/μm, respectively. The two-dimensional displacement sensor proposed in this paper offers the advantages of high detection precision, simple structure, and ease of implementation.

HPB SO72 - Predicting Major Intra-operative Blood Loss in Patients undergoing Liver Resection: A Machine Learning Radiomics Analysis Using Pre-Operative Liver CTs

Abstract Background Liver resection offers the best opportunity for curing patients with colorectal metastases and is an important treatment option for patients with hepatocellular carcinoma. However, it can be associated with significant morbidity and mortality, with one of the primary reasons being due to intra-operative blood loss which serves as an important predictor of post-operative outcomes. Predicting blood loss pre-operatively would be a powerful tool for clinicians in identifying higher risk patients. In this study, we examine whether radiomic features of the liver can predict major blood loss (>500 mls) alongside clinical and morphometric features in patients undergoing resection for colorectal metastases. Method Patient data was extracted from a prospectively maintained database of individuals undergoing resection for colorectal liver metastases (CRLMs). Radiomic features were extracted from pre-operative portal venous phase CTs. The background liver was randomly segmented in a two-dimensional plane away from cancer areas. Highly correlated features were dropped, and further feature selection techniques applied. Nested cross validation was performed to train and evaluate the machine learning models with the selected radiomic, clinical, and morphometric features. Results Radiomic features (159) were extracted from 106 patients, and 10 radiomic features comprised of first order and texture features, 3 morphometric, and 4 clinical features were selected for the machine learning models. The models demonstrated a robust ability to discriminate between major and minor blood loss. The best performing machine learning model demonstrated an AUC of 0.76 (95% CI 0.7-0.82). Other performance metrics for this model included a mean accuracy of 0.78 and an F1 Score of 0.87 on the validation data. Conclusion Pre-operative CT radiomic, clinical, and morphometric features have shown a modest ability to predict major intra-operative blood loss in patients undergoing hepatic resection for colorectal liver metastases. Further work is needed to validate and refine these models to improve performance. Additionally, we plan to incorporate data from other centres to validate our findings in further experiments to create a robust tool to guide surgical practice in this patient cohort.

Numerical investigation of soil arching and integral abutment bridge in a pile-supported railway embankment

ABSTRACT Rail transport plays a crucial role in promoting sustainable mobility and tackling environmental challenges. However, the construction of a railway track on soft soil poses significant challenges due to the inherent instability and potential for excessive settlement. To address these issues, this study numerically assessed a pile-supported embankment and an integral abutment bridge. Two different numerical models are simulated in two-dimensional (2D) plane strain conditions. Findings from numerical analyses of the pile-supported embankment revealed that soil arching is significantly influenced by embankment height and pile spacing. The maximum settlement of the embankment decreases with an increase in embankment modulus and friction angle. Furthermore, a correlation among soil arching indicators was established. Conversely, the analysis of integral abutment railway bridges (IARBs) indicates that the performance of the transition zone is significantly influenced by factors such as approach slab geometry and multiple axle passages.

Distributed Model Predictive Control Cooperative Guidance Law for Multiple UAVs

Aiming at the problem of multiple unmanned aerial vehicles (UAVs) cooperatively intercepting a maneuvering target, this paper proposes a cooperative guidance law with less energy consumption and a newly accurate time-to-go estimation algorithm in the two-dimensional (2D) plane. Firstly, based on the relative motion equations between UAVs and the target on the 2D plane, the line-of-sight (LOS) direction and the LOS normal direction models are established. Then, based on the distributed model predictive control (DMPC) theory, DMPC cooperative guidance laws are designed in two directions. This guidance law can ensure that all UAVs intercept the maneuvering target at the expected LOS angle at the same time and reduce the energy consumption during the guidance process. Then, a new time-to-go estimation algorithm is designed, which can reduce the time-to-go estimation error and improve the cooperative accuracy. Finally, the simulation results show that the DMPC cooperative guidance law reduces energy consumption by more than 50% compared to other guidance laws and the proposed time-to-go estimation algorithm improves the accuracy by 200% compared to traditional methods.

Wavelength dependence of linear birefringence and linear dichroism of Bi2−xPbxSr2CaCu2O8+δ single crystals

Copper oxide high-temperature superconductors, such as Bi2Sr2CaCu2O8+δ (Bi2212), have garnered extensive research interest due to their high critical temperatures (Tc) surpassing the Bardeen–Cooper–Schrieffer (BCS) limit. The two-dimensional CuO₂ plane is widely regarded as the most crucial element of high-Tc cuprate superconductors. The anisotropy of this CuO₂ layer remains a topic of ongoing interest. Although a few experimental results have reported strong optical anisotropy in both ab and ac-planes of Bi2212 through optical “reflectivity” measurements, there is a lack of studies focusing on the optical anisotropy of these materials using optical “transmittance” measurements by utilizing ultraviolet and visible light. Using a generalized high-accuracy universal polarimeter, we observed significant linear birefringence and linear dichroism peaks in the UV region at room temperature. To investigate the origin of the significant optical anisotropy, single crystals of Bi2−xPbxSr2CaCu2O8+δ with different lead contents (x = 0, 0.4, and 0.6) were grown using the floating zone method, and the wavelength dependencies of linear birefringence and linear dichroism along the c axis were measured. The insights gained into the optical anisotropy of Bi2−xPbxSr2CaCu2O8+δ from this study are significant for discussing its origin of the mechanism of high-Tc superconductivity.

Optimal Curve Fitting for Serial Chain in Six-Crease Origami Unit

Abstract Origami-inspired structures have been widely used in aerospace and robotics for three-dimensional (3D) symmetrical configurations using crease-symmetrical origami basic patterns. These patterns offer advantages in repeatable and systematic modeling and mass production. However, few studies have focused on 3D nonsymmetrical structures using symmetrical origami basic patterns due to their structure complexity, limiting their application. Therefore, we aim to analyze the folding behavior in 3D nonsymmetrical structures using a 6-crease symmetry origami base pattern. To achieve this goal, we first focus on behavior in a two-dimensional (2D) plane. This article presents a scheme for the behavior of origami units with an optimal curve-fitting algorithm. The curve can be any 2D space curve. The fitting curve, constructed by numerical analysis and an optimal approaching scheme, can satisfy error requirements and retain foldable origami unit features. The article verifies the feasibility of the curve-fitting scheme by presenting two curve examples, including a quadratic curve and a sin wave function. The results show that the fitting error is reduced by 99% when no boundary conditions are applied. This research provides valuable insights into understanding origami unit kinematic optimization through forward and inverse kinematics. It offers potential applications in the engineering design of foldable structures and precision origami-inspired mechanism, thereby opening avenues for further exploration of complex origami structures and their applications in emerging technologies.

Performance Analysis of Two-Dimensional Plane Diffusers at a Moderate Reynolds Number by Means of Unsteady RANS

Performance Analysis of Two-Dimensional Plane Diffusers at a Moderate Reynolds Number by Means of Unsteady RANS