Numerical Simulations Research Articles

Spoof surface plasmon Polaritons dual beam scanning antenna for 5G application

Dual beam scanning (DBS) antenna exited by two different spoof surface plasmon polaritons (SSPPs) transmission lines is proposed in this paper. The antenna is constructed by placing three rows of circular patches on both sides of two different planar SSPPs waveguide. These patches convert the SSPP guided waves into radiating waves. This simple single-layer antenna is characterized by dual without need to use switches or other complex configurations. It is designed to support application of several 5G sub-6 GHz bands (3.5 (n78) GHz, 3.7 (n77) GHz, and 4.5 (n79) GHz). The proposed antenna realizes the dual beam scanning by controlling the dispersion properties and field confinement along two different SSPPs transmission lines, based on different propagation constant. Numerical simulations are carried out by CST Microwave Studio and Ansys HFSS. These numerical simulations are verified by experimental results over the operating frequency band from 1 GHz to 6 GHz.

Aircraft ice accretion prediction based on geometrical constraints enhancement neural networks

Purpose The purpose of this study is to establish a novel airfoil icing prediction model using deep learning with geometrical constraints, called geometrical constraints enhancement neural networks, to improve the prediction accuracy compared to the non-geometrical constraints model. Design/methodology/approach The model is developed with flight velocity, ambient temperature, liquid water content, median volumetric diameter and icing time taken as inputs and icing thickness given as outputs. To enhance the icing prediction accuracy, the model involves geometrical constraints into the loss function. Then the model is trained according to icing samples of 2D NACA0012 airfoil acquired by numerical simulation. Findings The results show that the involvement of geometrical constraints effectively enhances the prediction accuracy of ice shape, by weakening the appearance of fluctuation features. After training, the airfoil icing prediction model can be used for quickly predicting airfoil icing. Originality/value This work involves geometrical constraints in airfoil icing prediction model. The proposed model has reasonable capability in the fast assessment of aircraft icing.

Influence of solid cylinders on fluid flow and thermal analysis in a curved channel with constant magnetic field

The current study explores the numerical simulation of constant mixed convection heat transfer and fluid flow within a channel, driven by the inlet velocity. The investigation focuses on a curved irregular channel where the presence of three differently sized circular obstacles introduces an unpredictable element to the heat transfer process. For the two-dimensional physical scenario, mathematical equations are formulated to analyze velocity and temperature. Employing appropriate dimensional variables, the coupled partial differential equations are transformed into dimensionless form. Subsequently, the Finite Element Method (FEM) is employed to simulate the results for non-dimensional physical parameters such as Reynolds number, Richardson number, Hartmann number, nanoparticles' volume fraction, and various states of the circular obstacles on heated lines, flow structure, velocities, and temperatures at mean positions generating isotherms, streamlines, velocity, and temperature profiles for various parameter increments. The analysis reveals significant influences of Reynolds number (Re) and heated circular obstacles on the temperature profile, manifesting as heated lines within the system. The analysis brings to light the substantial impacts of nanoparticles on the temperature profile at both the vertical and horizontal mean positions. An elevated Hartmann number signifies a more robust magnetic field than viscous forces. A heightened magnetic field can hinder fluid movement and modify the patterns of heat transfer. Based on the graphical results, we infer that temperature differences tend to arise between strata as the Richardson number increases, leading to a heightened and more evident stratification.

Inferences for the distribution of the duration of response in a comparative clinical study.

Duration of response is an important endpoint used in drug development. Prolonged duration for response is often viewed as an early indication of treatment efficacy. However, there are numerous difficulties in studying the distribution of duration of response based on observed data subject to right censoring in practice. The most important obstacle is that the distribution of the duration of response is in general not identifiable in the presence of censoring due to the simple fact that there is no information on the joint distribution of time to response and time to progression beyond the largest follow-up time. In this article, we introduce the restricted duration of response as a replacement of the conventional duration of response. The distribution of restricted duration of response is estimable and we have proposed several nonparametric estimators in this article. The corresponding inference procedure and additional downstream analysis have been developed. Extensive numerical simulations have been conducted to examine the finite sample performance of the proposed estimators. It appears that a new regression-based two-step estimator for the survival function of the restricted duration of response tends to have a robust and superior performance, and we recommend its use in practice. A real data example from oncology has been used to illustrate the analysis for restricted duration of response.

Experimental and Numerical Investigation on Group Anchor Performance of Wooden Bolts in Rammed Earthen Sites

ABSTRACT Challenges remain in understanding the interaction mechanisms and influencing factors of multi-anchor systems. To investigate this matter, this study conducted nine full-scale model experiments examining the pulling resistance and failure modes of wood bolts embedded in rammed earth. These experiments varied bolt numbers (2, 3, 4), spacings (500 mm, 1000 mm, 1500 mm), and embedment depths (200 mm, 300 mm, 400 mm). Key factors and their levels for the group anchoring effect in the model tests were determined through orthogonal analysis. Among these factors, embedment depth exerted the most significant influence on pulling resistance, followed by bolt spacing and number. Furthermore, a numerical simulation method for wooden anchor group systems was developed using the “contact surface” element in FLAC 3D finite difference simulation software. This method considered factors such as bolt number, spacing, edges, embedment depth, and the layered nature of the compacted soil. It analyzed stress distribution and transmission laws across various interfaces within the anchoring system and the compacted soil, thereby supplementing and expanding upon the findings of the model experiments. These findings enhance understanding of the complex interplay between multi-anchor systems and soil, providing a scientific foundation for analyzing mechanical behavior in similar anchoring applications.

Picosecond Femtojoule Resistive Switching in Nanoscale VO2 Memristors.

Beyond-Moore computing technologies are expected to provide a sustainable alternative to the von Neumann approach not only due to their down-scaling potential but also via exploiting device-level functional complexity at the lowest possible energy consumption. The dynamics of the Mott transition in correlated electron oxides, such as vanadium dioxide, has been identified as a rich and reliable source of such functional complexity. However, its full potential in high-speed and low-power operation has been largely unexplored. We fabricated nanoscale VO2 devices embedded in a broadband test circuit to study the speed and energy limitations of their resistive switching operation. Our picosecond time-resolution, real-time resistive switching experiments and numerical simulations demonstrate that tunable low-resistance states can be set by the application of 20 ps long, <1.7 V amplitude voltage pulses at 15 ps incubation times and switching energies starting from a few femtojoule. Moreover, we demonstrate that at nanometer-scale device sizes not only the electric field induced insulator-to-metal transition but also the thermal conduction limited metal-to-insulator transition can take place at time scales of 100s of picoseconds. These orders of magnitude breakthroughs can be utilized to design high-speed and low-power dynamical circuits for a plethora of neuromorphic computing applications from pattern recognition to numerical optimization.

Empirical approaches for non-linear site response: results for the ESG6-blind test

As a contribution to step 3 of the ESG6 blind prediction exercise, we present an application of two different, purely empirical approaches to estimate the strong ground motion at a soft site ("KUMA") from the observed ground motion at a reference rock site ("SEVO") for the two largest shocks of the Kumamoto 2016 sequence. The two methods estimate the non-linear transfer function between a reference rock and a sedimentary site by modifying the linear transfer function derived from weak motion recordings. The modification is based either on a machine learning tool based on a wide collection of Japanese weak and strong motion recordings and the associated site metadata (method 1), or on an estimate of a site-specific parameter related to an average non-linear site response (method 2). The acceleration time series are then derived at the sedimentary site of interest using an estimation of the time delay between wave arrivals at the rock and site stations, and a minimum phase assumption for the site transfer function. These predictions were made blindly, but after the ESG6 conference they could be compared both with the actual ground motion recorded at KUMA during the two shocks, and the average and range of all other predictions preformed for this benchmark. Both of these purely empirical methods provide an honorable prediction of usual engineering ground motion parameters of the two target events. The performance of these two purely empirical approaches is at least comparable to those of the numerical simulation methods for the foreshock—if not better—and slightly worse for the (largest) mainshock. As the methods required only recordings of weak motions at the target and a referent sites and very simple description of the soil profile. The use of moderate motions to constrain the frequency shift prediction for the second method and the consideration of an alternative phase modification are possible ways to improvement.Graphical

A simplified method for predicting overflow-induced crack propagation in gravity dams using genetic algorithm and material-based model

Cracks are always a serious concern in the stability analysis of gravity dams. One of the main reasons for the initiation of cracks is overflows. In evaluating dam safety under flood conditions, it is crucial to consider the balance between the strength of the dam body and the propagation of cracks. In this context, simplified equations serve as valuable tools in dam design as they offer a quick and efficient way to estimate the behavior of the dam structure. In this study, firstly using a polygonal material-based model (P-MBM), which is improved in considering the softening behavior of joints, the micro-crack propagation in masonry material is investigated. Then, based on performing 81 numerical simulations in a parametric study on the geometrical and geotechnical properties of the dam subjected to overflow, a great database of the behavior of different dams is investigated. Then, using the genetic algorithm, a set of equations is proposed, and their accuracy is validated through UDEC simulations and some theoretical methods from existing literature. For all models, the crack tends to be horizontal at the initial phase. Then, due to increasing the compressive stresses on the downstream side, the fractures tend to the dam toe. The results also indicate that the proposed equations can reasonably determine the behavior of gravity dams and the development of cracks in the dam body. The outcomes highlighted the considerable effects of geometry and geotechnical properties on dictating the trajectory of crack growth.

Modelling and numerical simulation of sequencing strategies for connected and autonomous vehicles at signal-free intersections

The signal-free intersections employ connected and automated vehicle technology to manage vehicles passing through the intersection. Due to conflicting traffic flows in opposition directions, a proper sequencing of Connected and Autonomous Vehicles (CAVs) at signal-free intersections becomes critical to impacting intersection traffic performance. Based on an examination of CAV queueing rules under the most common sequencing strategies of First-Come-First-Serve (FCFS) and Longest-Queue-First (LQF), commonly employed as benchmarks for evaluating diverse innovative approaches to signal-free intersections, we propose a Dynamic-Queue-Service (DQS) strategy that is tailored to accommodate high traffic demand. To explicitly elucidate the impact of diverse traffic demand in conflicting directions on the queue uncertainty and stochasticity of CAVs, as well as to investigate how various sequencing strategies influence the equity of CAV traffic at signal-free intersections with regard to CAV queueing dynamics under different strategies, we have developed a double-input traffic queueing model and derived a range of metrics, including the queue length, delay, conditional queue length, and variance of queue length. In addition, for the three strategies, we performed a series of numerical simulations to investigate the queueing process of CAVs at signal-free intersections. Numerical results show that under different levels of traffic demand in the conflicting directions, the FCFS, LQF, and DQS strategies output diverse traffic queueing performances, and the DQS strategy is confirmed to be well-suited for the situation of high traffic demand in both conflicting directions.

Vibration-based damage detection of beams using Hybrid Genetic Algorithm with combined l0 and l1 regularization

Vibration-based damage detection is an effective way of identifying beam damages before they become severe and potentially catastrophic. This paper introduces a novel and robust method for detecting multiple cracks in beams using a Hybrid Genetic Algorithm (HGA). The objective function of the proposed method, based on dynamic properties, can be employed with partial modal information and is enhanced by including the initial residuals between numerical and experimental models along with combined l0 and l1 regularization. This enhancement mitigates the impact of limited modal data, experimental noise, and modeling inaccuracies. Additionally, a method of selecting an appropriate regularization parameter by analyzing residual and solution norm curves is presented. The performance of the proposed method is evaluated and verified using both numerical simulations and experimental studies on a steel cantilever beam under four damage scenarios. In the experimental study, natural frequencies and mode shapes were determined under ambient vibration conditions using Enhanced Frequency Domain Decomposition (EFDD) and the Stochastic Subspace Identification (SSI) method. Finite element models of the beam were developed in ABAQUS software for numerical analysis, and a comparative study of numerical and experimental data was conducted. The proposed approach successfully identifies, locates and quantifies single and multiple damages in the beam, demonstrating its reliability and effectiveness, particularly in scenarios with limited modal data and significant experimental noise.

Heat transfer characteristics of printed circuit heat exchangers under mechanical vibrations

Purpose The purpose of this paper is to investigate the impact of mechanical vibration on the heat transfer and pressure drop characteristics of semicircular channel printed circuit heat exchangers (PCHEs), while also establishing correlations between vibration parameters and thermal performance. Design/methodology/approach By combining experimental and numerical simulation methods, the heat transfer coefficient and pressure drop characteristics of supercritical carbon dioxide (S-CO2) in a semicircular channel with a diameter of 2 mm under vibration conditions were studied. Reinforce the research by conducting computational fluid dynamics studies using ANSYS Fluent 22.0, the experimental results were compared with the numerical simulation results to verify the accuracy of the numerical method. Findings The use of vibration has the potential to attenuate the degradation of wall heat transfer caused by buoyancy-induced PCHEs on the upward-facing surface. The heat transfer enhancement (HTE) was maximized by an increase of 18.2%, while the pressure drop enhancement (PDE) was elevated by over 25-fold. The capacity to enhance the heat exchange between S-CO2 and channel walls through increasing vibration intensity is limited, indicating maximum effectiveness in improving thermal performance. Originality/value Conducting heat transfer experiments on PCHEs with mechanical vibration enhancement and verifying the accuracy of the vibration numerical model. The relation based on the dimensionless factor is derived. To provide theoretical support for using vibration to enhance the heat transfer capability of PCHEs.

Research on the Lubrication Performance of Hydrostatic Thrust Bearings Considering Dynamic Pressure Effect and Oil Film Pressure Loss

A lubrication performance mathematical model considering the dynamic pressure effect and pressure loss is proposed for stepped hydrostatic thrust bearings. The influence mechanism of rotational speed and load on the static pressure, dynamic pressure, pressure loss, total pressure, and total temperature of the clearance oil film is systematically discussed through a combination of theory-simulation-experiment. The investigation found that the total temperature of the oil film decreases with increasing load, increases with increasing rotational speed. The pressure loss also becomes increasingly significant with higher rotational speeds. The dynamic pressure is not limited by the load, but increases with the increase of rotation speed. The oil film pressure loss is jointly borne by static pressure and dynamic pressure within the range of 0-160rpm, and mainly borne by static pressure within the range of 160-200rpm. Additionally, the trends of static pressure, dynamic pressure, total pressure and temperature in experiment are nearly consistent with those predicted by numerical simulations, thereby validating the effectiveness of the research methodology employed in this paper.

Percolation of conditional dependency clusters based on edge-coupled interdependent networks

Considering the existence of multiple edge dependencies in realistic interdependent networks, we propose a model of edge-coupled interdependent networks with conditional dependency clusters (EINCDCs). In this model, the edges in network A depend on the edges in dependency clusters of size m in network B. If the failure rate of edges within the dependency clusters in network B exceeds the failure tolerance α, the corresponding edges in network A that depend on those clusters in network B will fail accordingly. By adopting the self-consistent probabilities approach, a theoretical analytical framework is established to quantitatively address this model. Specifically, we study the robustness of the system verified with numerical simulations in the effect of the cluster size and failure tolerance under random attacks on systems composed of two networks A and B constructed with Random Regular (RR), Erdös-Rényi (ER) and Scale Free (SF) models. Our results show that both networks A and B undergo a first-order or hybrid phase transition when the dependency cluster size does not exceed 2. However, when the cluster size of dependency clusters exceeds 2, a non-monotonic behavior is observed. In particular, when the failure tolerance is in the range from 0 to 0.5, the robustness of the system weakens with the growing in the number of dependency clusters of size 2. While, this tendency reverses when the failure tolerance is in the range from 0.5 to 1. Moreover, we observe that due to the asymmetric interdependency between the two networks, network B always undergoes first-order phase transition, whereas network A could exhibit different types of phase transitions, which depends on the size of dependency clusters. In addition, the failure tolerance may have opposite effects on the two networks with the growing of dependency cluster sizes. The conclusions of the study may provide useful implications and enrich the understanding in the robustness of edge-coupled interdependent networks.

Spurious Response Due to Linear Interpolation of Input Load and Some Remedies

ABSTRACT This study focuses on the analytical identification and quantification of one type of spurious responses in the context of response history analysis. The spurious response is caused by linear interpolation of input loads. Through analytical derivations and numerical simulations, it is shown that the identified spurious response is fully caused by the interpolation and can significantly affect both damping and inertial forces. Furthermore, the spurious response is not bounded, thus, resistance-based designs could potentially be non-conservative. The findings are applicable to (non-)linear MDOF systems. To address this issue and improve the quality of numerical results, remedies and recommendations are proposed.

Analysis of Graeco-Latin square designs in the presence of uncertain data

ObjectiveThis paper addresses the Graeco-Latin square design (GLSD) under neutrosophic statistics. In this work, we propose a novel approach for analyzing Graeco-Latin square designs using uncertain observations.MethodThis approach involves the determination of a neutrosophic ANOVA and the determination of the neutrosophic hypotheses and decision rule.ResultsThe performance of the proposed design is evaluated using the numerical examples and simulation study.ConclusionBased on the results observed, it can be concluded that the GLSD under neutrosophic statistics performs better than the GLSD under classical statistics in the presence of uncertainty.

Numerical simulation of the Co-combustion of coke and biochar coupled with methane injection in iron ore sintering processes

It is of great significance for cleaner production to partially replace traditional coke with biomass fuel in iron ore sintering processes. However, the higher reactivity of biomass leads to an unacceptable deterioration in sintering performance, which limits its high proportion application. This paper presents the numerical simulation of the technology of combining gaseous fuels and biomass for iron ore sintering. The improvement effect and mechanism of the methane injection method on the heat pattern and performance of the coke/biochar co-sintering bed were discussed. To more accurately quantify the coupling phenomena involved, the proposed model especially considers sub-processes of biomass combustion and gaseous reactions including volatile release/char formation, burning of the volatiles, and the oxidation and gasification of char particles. The results indicated that the equivalent methane heat injection method reached its limit of improvement at a concentration of about 0.6%, and failed to obtain qualified products. The thermal indicators and yield kept increasing within the concentration simulation range of 0∼0.8% under the extra methane method. At a concentration of 0.8%, peak temperature (PT), duration time (DTMZ), and enclosed area (MQI) in the high-temperature zone are 1442.094 K, 165.6 s, and 15923.72 K s, respectively, reaching the level of all coke method. The use of local concentration segregation can significantly optimize heat distribution and increase the yield of the coke/biochar co-sintering process.

Design and simulation analysis of an extrusion structure based on screw extrusion 3D printing

Abstract In response to the problems of 3D printing, such as uneven wire discharge and easy clogging of printing nozzles in FDM (Fused Deposition Modeling) printing technology, this paper develops a screw extrusion 3D printing melting deposition system based on simulation. The simulation results show that the maximum deformation of the screw occurs at the tail end, with a maximum value of 0.04 mm, while the fluid pressure and the pressure on the surface of the screw gradually increase along the direction of extrusion, and the maximum pressure occurs near the nozzle, with a value of 0.13 MPa. The fluid pressure is positively correlated with the screw speed and negatively correlated with the screw pitch. The fitting formula is obtained by numerical simulation of the screw speed and the flow velocity at the nozzle outlet. Using a self-made screw extrusion 3D printing equipment, relevant experiments are conducted to explore the influence of different layer thicknesses and line spacings on the mechanical properties of printed samples, as well as the influence of printing speed on surface quality. It is found that layer thickness has a significant impact on the bending strength of printed samples, with a maximum value of 24.74 MPa and a minimum of 19.21 MPa. The bending strength decreases by 28.79 % from 0.6 mm to 1.0 mm layer thickness. The line spacing has a significant impact on the tensile strength of printed samples, with a maximum value of 27.22 MPa and a minimum of 21.16 MPa. As the printing speed increases, the surface roughness of the printed piece also gradually increases from Ra = 389.28 μm at v = 30 mm/s to Ra = 535.45 μm at v = 70 mm/s, an increase of 37.55 %.

Accounting for friction in the mechanical testing of athletics tracks

This investigation deals with the problem of identifying the mechanical behaviour of rubbers from compression tests, performed on specimens having unfavorable geometry. A typical situation is that of flat specimens obtained from high-friction sports surfaces. To this purpose, experimental tests were conducted, aimed at measuring friction under various conditions and evaluating its effect on the compressive behavior of different rubber samples. The experimental results have been interpreted in view of an existing analytical model proposed by Gent and coworkers. The method was shown to be valid within a relatively broad range of conditions (in terms of materials, lubrication and aspect ratio). Its application allowed the creation of virtual “frictionless” curves, by rescaling experimental data for the stiffening factor predicted by Gent model. These curves represent more closely the intrinsic material behaviour, removing the large frictional contribution present in the experimental tests, and can be used as a more reliable input for numerical simulations.

Enhancing (quasi-)long-range order in a two-dimensional driven crystal.

It has been recently shown that 2D systems can exhibit crystalline phases with long-range translational order showcasing a striking violation of the Hohenberg-Mermin-Wagner (HMW) theorem, which is valid at equilibrium. This is made possible by athermal driving mechanisms that inject energy into the system without exciting long wavelength modes of the density field, thereby inducing hyperuniformity. However, as thermal fluctuations are superimposed on the non-equilibrium driving, long-range translational order is inevitably lost. Here, we discuss the possibility of exploiting non-equilibrium effects to suppress arbitrarily large density fluctuations even when a global thermal bath is coupled to the system. We introduce a model of a harmonic crystal driven both by a global thermal bath and by a momentum conserving noise, where the typical observables related to density fluctuations and long-range translational order can be analytically derived and put in relation. This model allows us to rationalize the violation of the HMW theorem observed in previous studies through the prediction of large-wavelength phonons, which thermalize at a vanishing effective temperature when the global bath is switched off. The conceptual framework introduced through this theory is then applied to numerical simulations of a hard-disk solid in contact with a thermal bath and driven out-of-equilibrium by active collisions. Our numerical analysis demonstrates how varying driving and dissipative parameters can lead to an arbitrary enhancement of the quasi-long-range order in the system regardless of the applied global noise amplitude. Finally, we outline a possible experimental procedure to apply our results to a realistic granular system.

The impact of lenses on the seepage failure of tailings dam.

The presence of lenses such as tailings slurry, frozen soil, and saturated zones disrupts the continuity of tailings dams and their normal seepage patterns, elevating the seepage line of the dam body and significantly impacting local stability. This study, to investigate how lenses affect the stability and failure mechanisms of tailings dams, employs numerical simulation and physical models and constructs a model of the tailings dam, incorporating tailings clay lens and void lens, to investigate variations in hydraulic gradients, seepage velocities, seepage flow, pore water pressure, and the patterns of seepage failure. This research reveals that the tailings clay lens within the dam body increases the hydraulic gradient in its vicinity due to its low permeability and raises the phreatic line. As the tailings clay lens approaches the dam body, the phreatic line tends to escape along the upper part of the lens towards the dam surface. In addition, the void lens could lead to a more pronounced seepage gradient along its path on the dam surface, with a liquefaction beneath it. As the void lens nears the toe of the slope, the dam failure mode transitions from a step-like progressive failure to an arch-shaped settlement failure along the void lens.