Two-dimensional Cross-section Research Articles

Waveguide finite element modelling for broadband vibration analysis of tyres including rotation and prestress

In the framework of tyre/road noise prediction, our aim is to introduce a waveguide finite element (WFE) method for broadband vibration analysis of rotating inflated structures of arbitrary cross-section. Approximating the geometry as perfectly circular, the finite element discretization is restricted to the two-dimensional cross-section, enabling fast and high-frequency computations. Tyres are particularly challenging to model due to various complicating effects, often approximated or neglected in WFE models : rotation, inflation, structural anisotropy, heterogenetity, damping among others. Our formulation uses Lagrangian perturbations of displacement in Eulerian coordinates, providing a concise way to express equilibrium equations in vibrating media initially moving, prestressed and subjected to fixed point forces (typically, contact excitations in rotating tyres). The method comprises three steps: computing the steady rolling state (including rotation, inflation and centrifugal force), determining the undamped vibration modes superimposed onto the steady state (solving an eigenvalue problem of quadratic type owing to Coriolis acceleration), and obtaining the forced response of the damped structure through specific orthogonality relationships (considering a specific form of damping). The WFE method is compared with a rotating shell analytical model from existing literature and is subsequently applied to a rotating tyre with heterogeneous cross-section up to 4kHz.

Computation of emitter-plasmon interactions using an axis-symmetric model for off-axis dipoles

The axis-symmetric modeling technique is based on expanding vector fields in cylindrical harmonics and computing the response on a two-dimensional cross-section separately for each azimuthal harmonic, significantly reducing computational costs. However, it has limitations when dealing with dipoles placed away from the symmetry axis due to challenges in the expansion of angular modes. To address this, we propose a reformulated axis-symmetric model based on the Fourier expansion of the delta function distribution concerning the azimuthal variable. This model is validated using standard Mie theory for off-axis dipoles and applied to study multiple-emitter-plasmon interactions. The emission properties of a non-cooperative ensemble near a plasmonic nanoparticle are observed to scale with the number of emitters considered, N. Notably, a Dicke effect-like superradiance (N2-dependence) is observed when a spatially disordered ensemble of dipoles oscillates collectively inside a plasmonic dimer gap. This kind of high-level cooperative quantum phenomenon is of high interest in fields such as quantum optics and light-harvesting.

Why gravity improves waterflood recovery in oil-wet and mixed-wet reservoirs

Most past experimental and numerical research on water flooding has demonstrated a reduction in oil recovery in gravity dominated flow: gravity leads to the water slumping to the bottom of the reservoir with earlier water breakthrough and poor sweep efficiency. However, these studies were all performed on strongly water-wet systems: wherever the water has gone, the oil is at residual saturation so a reduction in sweep efficiency gives a reduction in recovery. In reality few if any reservoirs are strongly water-wet. If the rock is mixed or oil-wet, gravity improves the local displacement efficiency. Gravity reduces the mobility of injected water forcing downward water movement and better oil displacement laterally. When gravity dominates, once water reaches the bottom of the reservoir, it moves upwards in a gravity-stable displacement, with improved local displacement efficiency that can be quantified by linear Buckley-Leverett analysis. We show, using fine-grid simulations of water flooding in a two-dimensional homogeneous vertical cross-section with typical fluid and rock properties, that the overall recovery after ∼0.3 pore volumes of water injected is higher than without gravity for heavy oil-wet (unfavourable mobility) applications. This improvement is greater in light oil-wet (favourable mobility) applications and occurs even before water breakthrough counteracting the negative effect of poor sweep efficiency. Simulations on a heterogeneous reservoir model representing an oil field from the Middle East confirmed the significance of gravity on improving the displacement and overall oil recovery. The same considerations should pertain in reverse for gas storage: storage efficiency improves in gravity dominated flow.

Dependence of wear of friction pairs of the mechanism for loading solid household waste into a garbage truck on the characteristics of antifriction materials

The article is dedicated to the establishment a regression dependence of wear of friction units of the mechanism of loading a garbage truck on the properties of antifriction materials. By using a first-order planning of experiment with first-order interaction effects using the Box-Wilson method, an appropriate regularity of wear of friction units of the garbage truck loading mechanism on the properties of antifriction materials has been determined. It is established that, according to the Student's criterion, among the studied factors of influence, the wear of friction units of the garbage truck loading mechanism is most influenced by the pressure in the friction zone, and the least – by the Brinell hardness of the antifriction material. The response surfaces of the objective function – wear of friction units of the garbage truck loading mechanism and their two-dimensional cross-sections in the planes of the influence parameters are shown, which allow to clearly illustrate the specified dependence of this objective function on individual influence parameters. It has been established that an increase in the pressure in the friction zone and sliding speed by 60% leads to an increase in the wear of friction units of the garbage truck loading mechanism during reverse motion by 6.3...34%, depending on the properties of antifriction materials. The expediency of conducting further research to determine ways to further improve the wear resistance of friction units of the mechanism for loading solid household waste into a garbage truck has been shown.

Development of a Real-Time Radiation Exposure Estimation Method Using a Depth Camera for Radiation Protection Education

X-ray fluoroscopy causes relatively high radiation exposure to physicians, radiation professionals, and patients. Understanding the behavior of scattered radiation is crucial for reducing occupational exposure. We developed a system for estimating radiation exposure during fluoroscopy by monitoring the position of the physician using a depth camera for radiation protection education. The dose distribution of scattered radiation in an X-ray room was simulated using Monte Carlo code. The data were displayed using augmented reality markers, and the dose at each joint point location was estimated using body tracking. Additional functions were created, such as displaying arbitrary two-dimensional cross-sections. The system performance ranged from 9.0 to 11.0 FPS with or without motion and a protective apron. The estimated doses were 0.93 to 1.21 times the measured doses for all joint points, except for the chest and pelvis. The estimated doses for the chest and pelvis were lower than the measured dose, with the minimum values being 0.72 and 0.60 times lower for the chest and pelvis, respectively. The system provides valuable insight into the estimation of radiation dose at joint points based on the physician’s position and movements, the physician’s optimal fluoroscopy location, and warning of dangerous exposure doses.

Stability of floating objects at a two-fluid interface

We explore the stability of floating objects at a two-fluid interface through mathematical modeling and experimentation. Our models are based on standard ideas of center of gravity, center of buoyancy, and Archimedes’ Principle extended to the two-fluid scenario. We investigate floating shapes with uniform, two-dimensional cross sections and identify analytically and/or computationally a potential energy landscape that helps identify stable and unstable floating orientations. We compare our analyses and computations to experiments on floating objects designed and created through 3D printing. Additionally, the paper includes open problems for further study.

Inertial particle focusing in fluid flow through spiral ducts: dynamics, tipping phenomena and particle separation

Small finite-size particles suspended in fluid flow through an enclosed curved duct can focus to points or periodic orbits in the two-dimensional duct cross-section. This particle focusing is due to a balance between inertial lift forces arising from axial flow and drag forces arising from cross-sectional vortices. The inertial particle focusing phenomenon has been exploited in various industrial and medical applications to passively separate particles by size using purely hydrodynamic effects. A fixed size particle in a circular duct with a uniform rectangular cross-section can have a variety of particle attractors, such as stable nodes/spirals or limit cycles, depending on the radius of curvature of the duct. Bifurcations occur at different radii of curvature, such as pitchfork, saddle-node and saddle-node infinite period (SNIPER), which result in variations in the location, number and nature of these particle attractors. By using a quasi-steady approximation, we extend the theoretical model of Harding et al. (J. Fluid Mech., vol. 875, 2019, pp. 1–43) developed for the particle dynamics in circular ducts to spiral duct geometries with slowly varying curvature, and numerically explore the particle dynamics within. Bifurcations of particle attractors with respect to radius of curvature can be traversed within spiral ducts and give rise to a rich nonlinear particle dynamics and various types of tipping phenomena, such as bifurcation-induced tipping (B-tipping), rate-induced tipping (R-tipping) and a combination of both, which we explore in detail. We discuss implications of these unsteady dynamical behaviours for particle separation and propose novel mechanisms to separate particles by size in a non-equilibrium manner.

Measurement of jet substructure in boosted tt¯ events with the ATLAS detector using 140 fb−1 of 13 TeV pp collisions

Measurements of the substructure of top-quark jets are presented, using 140 fb−1 of 13 TeV pp collision data recorded with the ATLAS detector at the LHC. Top-quark jets reconstructed with the anti-kt algorithm with a radius parameter R=1.0 are selected in top-quark pair (tt¯) events where one top quark decays semileptonically and the other hadronically, or where both top quarks decay hadronically. The top-quark jets are required to have transverse momentum pT>350 GeV, yielding large samples of data events with jet pT values between 350 and 600 GeV. One- and two-dimensional differential cross sections for eight substructure variables, defined using only the charged components of the jets, are measured in a particle-level phase space by correcting for the smearing and acceptance effects induced by the detector. The differential cross sections are compared with the predictions of several Monte Carlo simulations in which top-quark pair-production quantum chromodynamic matrix-element calculations at next-to-leading-order precision in the strong coupling constant αS are passed to leading-order parton shower and hadronization generators. The Monte Carlo predictions for measures of the broadness, and also the two-body structure, of the top-quark jets are found to be in good agreement with the measurements, while variables sensitive to the three-body structure of the top-quark jets exhibit some tension with the measured distributions. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Effect of variability of mechanical properties on the predictive capabilities of vulnerable coronary plaques

Background and Objective:Coronary plaque rupture is a precipitating event responsible for two thirds of myocardial infarctions. Currently, the risk of plaque rupture is computed based on demographic, clinical, and image-based adverse features. However, using these features the absolute event rate per single higher-risk lesion remains low. This work studies the power of a novel framework based on biomechanical markers accounting for material uncertainty to stratify vulnerable and non-vulnerable coronary plaques. Methods:Virtual histology intravascular ultrasounds from 55 patients, 29 affected by acute coronary syndrome and 26 affected by stable angina pectoris, were included in this study. Two-dimensional vessel cross-sections for finite element modeling (10 sections per plaque) incorporating plaque structure (medial tissue, loose matrix, lipid core and calcification) were reconstructed. A Montecarlo finite element analysis was performed on each section to account for material variability on three biomechanical markers: peak plaque structural stress at diastolic and systolic pressure, and peak plaque stress difference between systolic and diastolic pressures, together with the luminal pressure. Machine learning decision tree classifiers were trained on 75% of the dataset and tested on the remaining 25% with a combination of feature selection techniques. Performance against classification trees based on geometric markers (i.e., luminal, external elastic membrane and plaque areas) was also performed. Results:Our results indicate that the plaque structural stress outperforms the classification capacity of the combined geometric markers only (0.82 vs 0.51 area under curve) when accounting for uncertainty in material parameters. Furthermore, the results suggest that the combination of the peak plaque structural stress at diastolic and systolic pressures with the maximum plaque structural stress difference between systolic and diastolic pressures together with the systolic pressure and the diastolic to systolic pressure gradient is a robust classifier for coronary plaques when the intrinsic variability in material parameters is considered (area under curve equal to [0.91–0.93]). Conclusion:In summary, our results emphasize that peak plaque structural stress in combination with the patient’s luminal pressure is a potential classifier of plaque vulnerability as it independently considers stress in all directions and incorporates total geometric and compositional features of atherosclerotic plaques.

An Innovative Pipe Inspection Tool Utilizing Electromagnetic Resonance Coupling and Machine Learning

This paper describes an advanced tool that uses electromagnetic resonance coupling and machine learning techniques to detect and characterize metal loss on the inner surface of a metallic pipe. The proposed tool uses a transmitter coil placed along the axis of the pipe and four sensor coils installed around the transmitter coil. Any defect on the pipe surface leads to changes in the impedance of the transmitter and sensor coils as well as in the mutual coupling between them, thus creating a detectable variation in the outputs of one or multiple sensor coils. An artificial neural network is developed to reconstruct two-dimensional pipe cross sections and to completely characterize the defects using these variations. The proposed tool is tested and validated via simulations and data collected using an experimental prototype. Results show that the tool can fully characterize the size, location (azimuthal angle), and level (thickness) of metal loss.

Analysis of 3D pathology samples using weakly supervised AI

Human tissue, which is inherently three-dimensional (3D), is traditionally examined through standard-of-care histopathology as limited two-dimensional (2D) cross-sections that can insufficiently represent the tissue due to sampling bias. To holistically characterize histomorphology, 3D imaging modalities have been developed, but clinical translation is hampered by complex manual evaluation and lack of computational platforms to distill clinical insights from large, high-resolution datasets. We present TriPath, a deep-learning platform for processing tissue volumes and efficiently predicting clinical outcomes based on 3D morphological features. Recurrence risk-stratification models were trained on prostate cancer specimens imaged with open-top light-sheet microscopy or microcomputed tomography. By comprehensively capturing 3D morphologies, 3D volume-based prognostication achieves superior performance to traditional 2D slice-based approaches, including clinical/histopathological baselines from six certified genitourinary pathologists. Incorporating greater tissue volume improves prognostic performance and mitigates risk prediction variability from sampling bias, further emphasizing the value of capturing larger extents of heterogeneous morphology.

Physics-informed machine learning of multi-source monitoring data sparsely measured within a 2D vertical cross-section

Conventional machine learning (ML) methods suffer from several limitations, e.g., overreliance on large training datasets and poor performance in extrapolating beyond observations. Geotechnical monitoring data at specific sites are multi-sourced (e.g., settlement and horizontal displacement data). Moreover, each source of monitoring data may vary temporally and be sparsely measured, e.g., within a two-dimensional (2D) geological cross-section. Thus, effectively learning multi-source and limited monitoring data is difficult using existing ML methods. To address this challenge, this study proposes a physics-informed ML method combining geotechnical numerical models (e.g., the finite element model (FEM)) with sparse dictionary learning (SDL) methods. It uses a range of probable numerical model results corresponding to multiple, temporally varying responses in a 2D spatial range to construct a “dictionary” in SDL and employs multi-source and limited monitoring data to identify a few “atoms” from the constructed dictionary to improve model predictions. An engineering project for embankment construction is used to illustrate the proposed approach. Our results indicate that the proposed approach effectively integrates FEM results with multi-source and sparsely measured monitoring data and improves the predictions of multiple spatio-temporally varying geotechnical responses significantly, particularly those at subsequent time steps and unmonitored spatial locations within a 2D vertical cross-section.

Morphology of nanoporous glass: Stochastic 3D modeling, stereology and the influence of pore width

Excursion sets of Gaussian random fields are used to model the three-dimensional (3D) morphology of differently manufactured porous glasses (PGs), which vary with respect to their mean pore widths measured by mercury intrusion porosimetry. The stochastic 3D model is calibrated by means of volume fractions and two-point coverage probability functions estimated from tomographic image data. Model validation is performed by comparing model realizations and image data in terms of morphological descriptors which are not used for model fitting. For this purpose, we consider mean geodesic tortuosity and constrictivity of the pore space, quantifying the length of the shortest transportation paths and the strength of bottleneck effects, respectively. Additionally, a stereological approach for parameter estimation is presented, i.e., the 3D model is calibrated using merely two-dimensional (2D) cross-sections of the 3D image data. Doing so, on average, a comparable goodness of fit is achieved as well. The variance of the calibrated model parameters is discussed, which is estimated on the basis of randomly chosen, individual 2D cross-sections. Moreover, interpolating between the model parameters calibrated to differently manufactured glasses enables the predictive simulation of virtual but realistic PGs with mean pore widths that have not yet been manufactured. The predictive power is demonstrated by means of cross-validation. Using the presented approach, relationships between parameters of the manufacturing process and descriptors of the resulting morphology of PGs are quantified, which opens possibilities for an efficient optimization of the underlying manufacturing process. Published by the American Physical Society 2024

Determination of optimal technological parameters of a horizontal mixer of loose compound feeds

The quality of the compound feeds for animals and poultry directly depends not only on the components included in it but also on the type of mixer used. Horizontal mixers as compared to the vertical ones allow for a shorter period of time to obtain high-quality mixtures due to the intensification of the process of material movement by belt working bodies. The aim of the research is to determine optimal technological parameters of a horizontal mixer with a 0.3 m3 mixing chamber with a belt working body. The mixer is designed to produce mixed compound feeds of high uniformity in production lines, workshops or can be used as an independent machine for mixing loose components. The research was carried through multifactorial experiment. As the result, mathematical models of the mixer working process were obtained, two-dimensional cross sections of the response surfaces were built. The obtained mathematical models make it possible at the design stage to identify the dependence of qualitative and energy indicators on factors at the considered levels of variation. According to the results of the multifactorial experiment, it has been established that the best mixing quality of 94.8 % is achieved when the mixing chamber is loaded by 58 % at a speed of rotation of the mixer shaft of 30 min-1, mixing time of 6 minutes with simultaneous supply of the control and the main components. At the same time, the throughput is 0.78 t/h, and the specific energy consumption is 2.04 kWh/t.

Investigation of the stability of a fly ash pond facility using 2D and 3D slope stability analysis

A numerical investigation of the effect of pore pressure regime on the safety factor and the critical failure mechanism is presented for fly ash storage facility. Pore pressures’ measurements from standpipe piezometers and pore pressure estimated from seepage analysis are used to compare the factor of safety for a fly ash slope. This was applied for considering static and seismic scenarios. A probabilistic approach was applied to account for the uncertainties resulting from the limited data available and support a qualitative risk assessment evaluation. Slope stability analysis is conducted in two and three dimensions, adopting the limit equilibrium analysis approach, and also a finite element seepage analysis, to assess the stability of the slope. The two-dimensional cross-sections were extruded to three-dimensional models to estimate the factor of safety and associated shear failure. The results from the performed analysis suggest an increase in safety factor values of 5%.

Visualization of water transfer channel in sludge dewatering conditioned with skeleton builders by X-ray micro-computed tomography

Skeleton builders were normally deemed to improve the high porosity and newly-generated permeability of sludge cakes by building water transfer channel during high pressure filtration, thus enhancing sludge dewaterability. However, currently a direct visualization proof of water transfer channel was still lacking. This study provided the direct proof for visualizing water transfer channel in dewatered sludge cakes conditioned with a typical skeleton builder (i.e., phosphogypsum (PG)) by X-ray micro-computed tomography (micro-CT) for the first time. After the addition of PG, the pixel value and image luminance increased significantly, indicating the presence of high density substances from both two-dimensional (2D) cross section and three-dimensional (3D) reconstruction CT images. Moreover, the CT numbers showed strong and negative correlations with specific resistance to filtration (SRF) (R = − 0.99, p < 0.05), capillary suction time (CST) (regression coefficient (R) = − 0.87, probability (p) < 0.05), and water content of the dewatered sludge cake (R = − 0.99, p < 0.05), respectively. These results indicated that the X-ray micro-CT could be a potential technique for analyzing the water distribution in sludge samples conditioned with skeleton builders.

Representation and interpretation about underwater sound speed gradient field in the GNSS-A observation

SUMMARY The Global Navigation Satellite System—Acoustic ranging combination technique (GNSS-A) is a seafloor geodetic observation technique that achieves an accuracy of centimetres by combining high-rate GNSS data with acoustic ranging. The technique determines the seafloor position by acoustic ranging between the sea surface and multiple seafloor stations, using GNSS data from the sea surface station. Here, the gradient state of the underwater sound speed structure (SSS) is a significant source of error. The open-source software GARPOS can reduce the effect from underwater gradient structures by retrieving the underwater disturbance as a parameter projected onto the sea surface and seafloor. To evaluate the effects of underwater disturbances, a quantitative comparison of the model parameters is necessary. In this study, we developed a representation method to evaluate features of the ocean field. Here, the expression method was described in the order of a formulation and an interpretation in the case of a 2-D cross-section and extension to the case of an actual 3-D field. This method makes it possible to evaluate SSS states in the GNSS-A observations. As an example, we showed the correlation between the anomaly of the expressed ocean state and the anomaly of the seafloor station position, showing that this expression method is an effective index for correcting bias errors. Additionally, we used the data from sites located in the Kuroshio area, a strong current near Japan, to show that the ocean state can be quantitatively interpreted using this expression method.

Analysis of two-dimensional magnetotelluric inversion for the delineation of the petroleum system in the Kutai basin, East Kalimantan, Indonesia

The Kutai Basin in East Kalimantan is known as a potential area for oil and gas exploration. Two-dimensional magnetotelluric (MT) analysis is applied to investigate the geological structure and distribution of subsurface resistivity. This study aims to delineate the petroleum system using MT data and identify zones with potential for the accumulation of hydrocarbons. MT data has been collected at several strategic locations in the Kutai Basin, and two-dimensional cross-sections have been constructed to obtain vertical resistivity imaging at several depths. In this study, there were nine measurement points located on one line. The data is then inverted to obtain a two-dimensional resistivity model, which qualitatively represents the subsurface structure. The results of this study indicate that there is a low resistivity anomaly zone that identifies the presence of source rock with a resistivity value of 1-12 Ωm. In this line, it is suspected that the petroleum system that allows trapped hydrocarbons is found in the area, below the KT36 and KT13 measurement points. In this area there are folded structures in the form of synclines and anticlines, which raises suspicions about the types of traps formed from structural traps.

Research on the conductivity and self-sensing properties of high strength cement-based material with oriented copper-coated steel fibers

In this paper, a cement-based sensor for monitoring the performance of high-strength concrete was prepared by adding 0.5 vol%, 1.0 vol%, 1.5 vol%, and 2.0 vol% copper-coated steel fibers (CCSF) as conductive fillers. The fresh cement-based mixture was poured into a funnel-type fiber alignment device, which used its fluidity of the mixture to achieve an aligned distribution of shear-induce fiber within the cementitious matrix. The analysis results indicate that the cement-based sensor with fiber oriented distribution exhibits enhanced electrical conductivity and lower percolation threshold. In addition, the aligned CCSF in the cement matrix mitigates the impact of temperature on resistivity. The resistivity and temperature of the copper-coated steel fibers cement-based sensors (CSFCS) between 5 °C and 70 °C conform to the Arrhenius relationship. The specimens with aligned fibers demonstrate greater flexural strength compared to those with randomly distributed fibers. Additionally, they also reflect greater piezoresistive response, including higher sensitivity, better repeatability as well as less hysteresis time. Through the two-dimensional cross-section analysis, the angle between CCSF and the cross-section of the fiber-aligned specimen is significantly reduced, and the fiber orientation factor and fiber orientation coefficient increased considerably. The funnel device for preparing fiber-reinforced cement-based materials can effectively improve fiber orientation.

A Modified Approach to the Rack Generation of Beveloid Gears

The purpose of this paper is to present an easier and more efficient method for the determination of the geometry of a bevelled gear tooth. Based on a method that provides an easier way for the rack generation of involute helical gears, the mathematical model of a beveloid gear is studied. The mathematical procedure for developing two-dimensional cross-sections has been extended to three-dimensional gear models. A computer programme is developed to obtain generating and generated surfaces. The proposed algorithm is compared with the previous studies for verification and validation. The results demonstrate that the coordinates obtained from the given method are nearly the same on the start and end points of the main gear parts, such as the involute and root fillets regions. Also, between the limits, the values can be considered acceptable. A coordinate deviation of the gear profile has been observed in the mathematical model, because of the profile shift. Modifications have been developed in the equations to eliminate these cases. The main advantage of the proposed method is to obtain mathematical models without carrying out some of the calculation steps used in previous studies. Eventually, this feature will provide an easier and faster method to develop computer-aided models of the beveloid gear types.