Three-dimensional Analytical Model Research Articles

Research on the Calculation Method for the Load Distribution of the Dual-Input Counter-Rotating Transmission System

In order to solve the problem of an uneven load distribution in a double-input and double-output gearbox, based on the small-displacement Jacobi spin theory and considering the manufacturing and assembly errors of the gearbox, a Jacobi spin analysis model of the gearbox was established. In order to improve the accuracy of the three-dimensional tolerance analysis of the gearbox, on the basis of the processing method of parallel chain of gears and shafts and box and shafts, the serialization method of parallel chain of meshing gear pairs is proposed, and the gearbox was established. For the three-dimensional tolerance analysis model, three-dimensional tolerance analysis was carried out on the side-clearance dimensions of double-input and double-output gearboxes, and the side clearance values under the extreme value method and Monte Carlo method were deduced and combined with the theoretical side clearance to obtain the range of the side clearance of the gearboxes. Elastic deflection analysis was carried out on the gearbox shaft system, and the compensation relationship between the elastic deflection and the side clearance was investigated, so as to calculate the range of the value of the gearbox uniform load coefficient from 1 to 1.259. The error between the theoretically calculated uniform load coefficient and the experimentally tested uniform load coefficient was 6.61%, which verifies the reasonableness of the load distribution method of double-input and double-output gearboxes calculated using three-dimensional tolerance analysis combined with the elastic deflection angle, and provides a theoretical basis for the optimal design of the uniform load of multi-branch input gearboxes.

Enhancing the performance of thermoelectric generators using novel segmental arrangement of multi-functional gradient materials

Enhancing the performance of thermoelectric generators at wide range of operating temperatures is of great importance to maximize the output power. Thus, different updated semiconductor materials with different values of figure of merit are used. Accordingly, a modified design of the TEG system based on the multi-functional gradient (MFG) technique is developed. A comprehensive three-dimensional modeling and optimization analysis was developed and numerically simulated. The numerical predicted results were validated using the available measurements and numerical data. The results showed that when compared to low operating temperature semiconductor material of traditional (Bi2Te3) at a hot side temperature equals 227 °C, the updated material improved the output power and efficiency by 18.8% and 58%, respectively. At high operating temperature at Th = 620 °C, the upgraded material outperformed the Silicon–germanium (SiGeT) traditional semiconductor material by about 71% in the output power and 100% in the efficiency. Using the MFG-TEG, the performance improvement over the conventional design at Tc = 27 °C, and Th of 477 °C was around 315% for output power and 503% for efficiency. The current findings introduce a brand-new, innovative technique that allows scientists to create thermoelectric generators that are incredibly efficient.

A new 3D asymmetric double-Gaussian wake analytical model for horizontal-axis wind turbines

A new three-dimensional analytical model named 3DADG that is able to describe asymmetric evolution of wind turbine wake is proposed in this paper. Due to the combined effects of wind wheel rotation and wind shear effects wake attenuation shows asymmetric properties. However, existing wake analytical models fail to describe such unique properties. To solve this problem, spatial dependencies of the wake expansion rate and deficit coefficient are revealed to successfully present horizontal attenuations of the wake varying from asymmetric-double-Gaussian in the near and transition wake regions, and then to single-Gaussian in the far wake region. The wind shear effect is also considered in the model to include asymmetric vertical wake speed attenuation. This model is derived from the laws of mass and momentum conservation. It is verified through comparisons with the results of wind tunnel “blind test” and LES simulation. The model proposed is capable to show spatial evolution of wind turbine wake from a three-dimensional perspective. Sensitivities of thrust coefficient and turbulence intensity to the model are also investigated. It not only promotes development of wake analytical model but also provides a useful tool for power prediction and wake control of wind farms under wake effects.

Reversible Morphological Remodeling of Prefrontal and Hippocampal Serotonergic Fibers by Fluoxetine.

Serotonin-releasing fibers depart from the raphe nuclei to profusely innervate the entire central nervous system, displaying in some brain regions high structural plasticity in response to genetically induced abrogation of serotonin synthesis. Chronic fluoxetine treatment used as a tool to model peri-physiological, clinically relevant serotonin elevation is also able to cause structural rearrangements of the serotonergic fibers innervating the hippocampus. Whether this effect is limited to hippocampal-innervating fibers or extends to other populations of axons is not known. Here, we used confocal imaging and three-dimensional (3-D) modeling analysis to expand our morphological investigation of fluoxetine-mediated effects on serotonergic circuitry. We found that chronic treatment with a behaviorally active dose of fluoxetine affects the morphology and reduces the density of serotonergic axons innervating the medial prefrontal cortex, a brain region strongly implicated in the regulation of depressive- and anxiety-like behavior. Axons innervating the somatosensory cortex were unaffected, suggesting differential susceptibility to serotonin changes across cortical areas. Importantly, a 1-month washout period was sufficient to reverse morphological changes in both the medial prefrontal cortex and in the previously characterized hippocampus, as well as to normalize behavior, highlighting an intriguing relationship between axon density and an antidepressant-like effect. Overall, these results further demonstrate the bidirectional plasticity of defined serotonergic axons and provide additional insights into fluoxetine effects on the serotonergic system.

Analytical analysis of the thermal comfort of the occupants inside a truck cabin

Thermal comfort inside a truck cabin is a parameter that influences the well-being of the driver and passengers. From the very first steps of designing the driver’s seat of a vehicle, the driver’s well-being is taken into account through ergonomic parameters. To analyze the ultimate comfort inside a truck cabin, a simplified sketch of the cabin will be proposed. The three-dimensional analytical calculation model is solved using the Ansys program in the Fluid Flow (CFX) module. Through modeling and numerical simulations, the temperature inside a truck cabin, the mode of movement of the air flow and the speed of the air flow are determined. Following these tests, it is checked whether the thermal comfort conditions for the driver and passengers in a truck cabin are respected and fulfilled. These term comfort conditions are evaluated based on some comfort indices available in specialized literature.

Investigating a three-dimensional convolution recognition model for acoustic emission signal analysis during uniaxial compression failure of coal

Acoustic emission predicts coal sample failure, vital for early warnings and monitoring. The study emphasizes using acoustic emission to predict coal sample failure patterns and establish a discriminative model for monitoring. It employs a lightweight 3D convolutional model combining DenseNet with Group Convolution (GC) and the "squeeze-and-excitation" (SE) module. Coal samples from Xinglongzhuang Coal Mine underwent uniaxial compression, and a subset of experiments with prominent features was selected. The resulting acoustic emission parameters were then transformed into spatiotemporal image sequences for input to the model. Successfully identifying hazardous coal damage stages, all four network structures (DenseNet, DenseNet + GC, DenseNet + SE, DenseNet + GC + SE) achieved over 98.29% predictive accuracy in verification samples. The model exhibited a recall rate of over 98.02% for high-risk samples, effectively capturing spatiotemporal information. DenseNet + GC + SE showed a probability distribution focusing on different risk levels. By integrating group convolution and SE modules, this model significantly reduced both model and time complexity while preserving precision, enhancing efficiency. It effectively discerns diverse acoustic emission features through group convolution and evaluates their significance using the SE module. Compared to the traditional C3D neural network, this model greatly reduces complexity and time requirements while improving efficiency in distinguishing between various damage stages.

A novel intraocular pressure predicting method based on hyperelastic mechanical model of cornea

Measuring intraocular pressure (IOP) is crucial and remains challenging in diagnosing glaucoma, as it is associated with cornea deformation during inflation. In this study, a three-dimensional analytical model based on hyperelastic constitutive relationship to predict correlation between cornea vertex displacement and the IOP is proposed. The analytical model is validated by rigorous experiments. Rabbit corneas were selected for this study and their mechanical properties were obtained using uniaxial tensile tests. To mimic the environment in which the cornea exists, an artificial anterior chamber equipped with water-injection pipelines was constructed to study the relationship between the corneal vertex displacement with IOP value in practical situation. The experimental results of rabbits corneas prove that the IOP can be deduced based on the measured corneal vertex displacement by the analytical model. Furthermore, subtle difference occurs when comparing the calculated human IOPs with those measured by medical equipment, demonstrating that the proposed method is suitable for monitoring the IOP of human. This novel IOP predicting method provides new inspiration for the design of eyepieces, as well as the preoperative preparation for laser surgery and evaluation of corneal damage.

Three-dimensional modelling and morphometric analysis of skull of badger (Meles meles) with computed tomography images.

Morphometric measurements help to understand the skull morphology in different animal species, detect skull deformations and figure out their causes. The aim of this study is to make a three-dimensional (3D) modelling of the badger skull using computed tomography, to show its anatomical structures and to reveal the morphometric measurement values. Skull measurements were carried out using a digital calliper at 27 measurement points based on metric measurement points. After the scanned images were stored in Digital Imaging and Communications in Medicine format, they were transferred to MIMICS 20.1 (The Materialize Group) programme and 3D models the skulls were created. The surface area and volume values of the skulls were calculated on these models. The volume and surface area parameters were expressed as mean±SE. Four different indices were calculated using osteometric measurements. Statistical analyses were made by determining the mean value and standard deviation of the examined properties and the correlation coefficients among these properties. In the metric measurement points taken as a basis, the longest measurement in the skulls was the total length and its mean value was 124.60±0.64mm. The shortest measurement was the breadth dorsal to the external auditory meatus, and its mean value was 6.75±0.24mm. Consequently, statistical differences in the craniometric values of badgers' skulls were determined by using CT and 3D modelling software. In addition, it was concluded that the badger skull can be easily distinguished from other carnivore species by carrying out morphometric measurements.

Influence of Biotite Content on the Mechanical Response of Granite Using a Novel Three-Dimensional Grain-Based Model and Force Chain Analysis.

In this study, a three-dimensional grain-based model based on the discrete element method is utilized to replicate the heterogeneous structure of crystalline granite, and corresponding laboratory tests are conducted to validate the numerical conclusions. A novel model and an analytical method involving a multilevel force chain network are employed to quantitatively investigate the influence of mineral content on the mechanical behavior of granites. First, a set of granite specimens with varying biotite contents is constructed, and then, uniaxial compression tests are conducted. The effects of the mineral content on the mechanical behavior, force chain network characteristics, and fracture resistance of granite specimens are quantitatively analyzed. The results indicate an inverse relationship between the biotite (VB) content and the load-bearing capacity of granite under uniaxial compression conditions. As VB increases, the number of contacts within the biotite structure increases, as does the force chain distribution density within the biotite structure, while the force chain distribution density in other intragranular structures correspondingly decreases. The average values and sum values of all of the force chains in the whole specimen decrease with increasing VB. Among the various structures, intragranular structures exhibit the highest fracture resistance, whereas intergranular structures exhibit lower resistance.

GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data

Abstract. Borehole data are essential for conducting precise urban geological surveys and large-scale geological investigations. Traditionally, explicit modelling and implicit modelling have been the primary methods for visualizing borehole data and constructing 3D geological models. However, explicit modelling requires substantial manual labour, while implicit modelling faces problems related to uncertainty analysis. Recently, machine learning approaches have emerged as effective solutions for addressing these issues in 3D geological modelling. Nevertheless, the use of machine learning methods for constructing 3D geological models is often limited by insufficient training data. In this paper, we propose the semi-supervised deep learning using pseudo-labels (SDLP) algorithm to overcome the issue of insufficient training data. Specifically, we construct the pseudo-labels in the training dataset using the triangular irregular network (TIN) method. A 3D geological model is constructed using borehole data obtained from a real building engineering project in Shenyang, Liaoning Province, NE China. Then, we compare the results of the 3D geological model constructed based on SDLP with those constructed by a support vector machine (SVM) method and an implicit Hermite radial basis function (HRBF) modelling method. Compared to the 3D geological models constructed using the HRBF algorithm and the SVM algorithm, the 3D geological model constructed based on the SDLP algorithm better conforms to the sedimentation patterns of the region. The findings demonstrate that our proposed method effectively resolves the issues of insufficient training data when using machine learning methods and the inability to perform uncertainty analysis when using the implicit method. In conclusion, the semi-supervised deep learning method with pseudo-labelling proposed in this paper provides a solution for 3D geological modelling in engineering project areas with borehole data.

Development and Validation of a 3-D Analytical Fluidic Model in Cartesian Coordinates for a Magnetic Refrigeration Application

This paper focuses on the development and validation of a three-dimensional (3-D) analytical model based on the formal resolution of the incompressible Navier-Stokes equations in Cartesian coordinates. This analytical fluidic model calculates the evolution of the fluid flow velocity for various pressure gradient shapes (i.e., square, trapezoidal, ramp, triangle, sinusoidal signals, etc.), with or without mean value, using Fourier series. The model can consider square and rectangular channels of any dimensions in terms of height, width, and depth. It allows for the study of different types of fluid flow and geometries. The introduction highlights the significance of analytical modeling, particularly in the context of Magnetic Refrigeration (MR) technologies. The model assumptions and governing equations are presented. The results obtained from the analytical model are validated and show good convergence with those obtained using the COMSOL Multiphysics® software. The comparison demonstrates a high level of agreement between the two models. The analytical model performs well in terms of computation time and accuracy. It will be coupled with an analytical thermic model and used to optimize Active Magnetic Regenerative Refrigeration (AMRR) cycles. The ultimate objective is to determine an optimal pressure gradient evolution in order to maximize heat exchange in a regenerator channel.

Three-dimensional modeling and geostatistical structural analysis for ore deposit prospecting trend and wisdom mining: a case study in the Jiaoxibei gold field, China

The orientation of deep-seated orebodies was observed shifted from the northwest to north at the Xincheng deposit in the Jiaoxibei gold field during the mining operations. To make informed decisions, understanding the geological factors influencing this directional change is crucial for mining engineers. Prior research suggested that the ore-controlling fault morphology might correlate with the orebody positions and the thickness of alteration zones. Hence, the morphology of fault structures emerges as a key point in this work. First, we constructed a three-dimensional (3D) fault surface model. A large fault framework was interpreted using gravity–magnetic–electrical geophysical datasets, and then, the local details of the fault surfaces were characterized using an interpolation method based on the drillhole fault gouge data. Subsequently, we statistically assessed the spatial association between fault morphology and orebody positioning using the standardized C-values method and demarcated the ore-controlling structures on fault surfaces using quantitative indicators. The indicators of fault dips, fault azimuths, and the second-order trend residuals of fault surfaces represented the fault morphology. The drillhole grade data (Σsampling grade * sampling length) were used to describe the scale of mineralization zones, and the cumulative thickness of the pyrite–sericite altered rocks indicated the intensity of alteration zones. Finally, a geostatistical structural analysis was used to depict the mineralization orientation at different locations. Through these methods, we aim to propose a potential pattern of how ore-controlling fault morphology spatially influences the positions and orientations of orebodies. This comprehensive approach offers valuable insights into exploring deep-seated mineralization at the Xincheng deposit, aiding in a better understanding of the deposit’s geological dynamics for future mining endeavors.

Three-Dimensional Accurate Geometric Modeling and Mechanical Analysis of Wire Mesh for Deployable Antennas

Wire meshes are widely used in deployable antennas, and the structure of the wire mesh directly affects the structural and electrical properties of the antenna. This study proposes a set of automated geometric modeling and mechanical analysis processes to realize the automated mechanical analysis and design of complex wire mesh structures. First, considering the tilt in the wire mesh structure owing to the traction of the underlap on the loop, a three-dimensional (3D) geometric model of the repeating unit of the wire mesh structure was established using periodic cubic spline curves. Subsequently, a method using sensitivity matrix adjustment is proposed to eliminate the interstructure inlay phenomenon, and an optimization model is established. The vector superposition method established a 3D geometric model of the overall wire mesh structure without an inlay problem. Finally, a finite element model of the wire mesh considering the contact problem was established by the adaptive matching method for contact pairs of the finite element model of the wire mesh. Mechanical simulation experiments were carried out on the model, comparing the theoretical analysis with the experimental results and verifying its reasonableness.

Deep gold prospectivity modeling in the Jiaojia gold belt, Jiaodong Peninsula, eastern China using machine learning of geometric and geodynamic variables

Gold mineralization in the Jiaojia gold belt was formed in a structurally-dominant hydrothermal mineral system showing a close spatial association with the Jiaojia detachment fault. This study delves into the Jiaojia gold belt from the perspective of coupled spatial association and ore-forming processes by employing spatial analysis of three-dimensional (3D) models, 3D ore-forming numerical modeling, and 3D prospectivity modeling using machine learning techniques (random forest (RF) and multilayer perceptron (MLP)). The overarching goal is to gain insight into the structural-hydrothermal gold system and pinpoint potential areas of deep-seated gold deposits for future exploration endeavors. The spatial analysis of ore-controlling faults uncovers a close correlation between gold enrichment and specific fault geometrical attributes, including a dip angle ranging from 20° to 40°, minimal variations in dip angle (less than 5°), and convex topographical features. These attributes likely stem from the influence of fault morphology on the flow and pooling of fluids. In conjunction with this, 3D ore-forming numerical modeling of structural deformation and fluid flow reveals that gold mineralization is intertwined with moderate volumetric strain and shear strain of rock and fluid divergence. This interaction seems particularly pronounced in areas characterized by channel-like or gentle features. Consequently, it is plausible that gold distribution in the Jiaojia region is the outcome of a comprehensive coupling process involving strain localization, rock deformation, fluid flow, heat transfer and/or interaction. The deep gold prospectivity models of RF and MLP for the Jiaojia district jointly using the predictive variables of fault geometry features and ore-forming simulation data (volume strain, shear strain, temperature variation, and fluid flux) exhibit higher AUC (area under the curve) values compared to models employing individual predictor variable datasets. This improvement underscores their enhanced predictive capability. The prospectivity results thus were used for identifying gold potential within the Jiaojia region, where five promising gold targets at depth were ultimately determined.

An advanced three-dimensional analytical model for wind turbine near and far wake predictions

Most existing analytical wake models have been designed to represent the velocity distribution of the far wake region behind a wind turbine, but fail to reproduce the trend of the near wake. In order to meet the demand for both near and far wake velocity predictions, a concise three-dimensional dual-cosine shape (3D-COU) model is proposed. Moreover, by taking into account the wind shear and ground effects in the vertical direction, this model is capable of describing the anisotropic property of the 3-D wake field and is much closer to the reality. The proposed model is then calibrated and validated through a series of test cases, including different scales of turbines that are operating under a wide range of inflow conditions, and meanwhile the reference data resource is diverse. Overall, the results demonstrate that the 3D-COU model can accurately predict the variations of the wake velocity in both the vertical and horizontal directions throughout the whole wake region. Given its good accuracy, simplicity and applicability, this model provides the potential to effectively address practical problems in wind energy projects.

Three-dimensional creep calculation model for reliability analysis of concrete-filled steel tubular (CFST) structure

For long-span concrete-filled steel tube (CFST) structure, it is essential to implement efficient and realistic prediction models for the long-term processes of core concrete creep. In order to systematically study the main influential factors in CFST structure creep effects, a probabilistic analysis can be performed. The objective of this paper is to analyse the long-term response of CFST structure by using time-dependent reliability method. To address the problem of creep calculation, a novel and comprehensive presentation was developed. By converting the integral-type creep law to a differential-type form with internal variables, based on the Kelvin chain model, an elastic structural analysis with generally orthotropic elastic moduli and eigenstrains was established. We have compiled a three-dimensional (3-D) finite-element analysis programme that considers the creep Poisson effect of core concrete to analyse the long-term performance of the CFST structure. This is achieved by developing a commercial finite element code, such as Usermat in ANSYS. As calculation examples, several time-dependent analyses of a CFST stub column and long-span CFST arch bridge were performed. The calculated results of long-term behaviour agree well with experimental and measured data. Considering the randomness of various input parameters, such as physical dimensions and materials of the CFST structure, we have analysed the uncertainty using the Latin-hypercube-sampling (LHS) stochastic finite-element method. The results of creep sensitivity analysis revealed that coefficient of creep model uncertainty, steel and concrete elastic modulus were the three most influential parameters for CFST stub columns’ creep, and load, coefficient of creep model uncertainty, relative humidity, steel and concrete elastic modulus were the five for CFST arch bridges’ long-term deflection. In addition, the use of Monte Carlo (MC) and response surface (RS) methods for structural stochastic reliability analysis demonstrates the ability of these approaches to assess the reliability index of long-span CFST arch bridges. This provides a valuable reference for the design and performance evaluation of CFST structures.

Inductance Analysis of Transverse Flux Linear Synchronous Motor for Maglev Trains Considering Three-Dimensional Operating Conditions

Despite the availability of powerful finite element method (FEM) tools, an accurate and fast analysis method is needed in the early design stage to find an initial motor design structure with the expected performance. When it is applied to maglev trains, inductance of the transverse flux linear synchronous motor (TFLSM) is affected by the cogging structure, the change of air gap length and the variation of lateral offset. Therefore, the analytical method of inductance in the TFLSM is different compared to that in the conventional rotating field winding motors. The three-dimensional (3-D) analysis models for obtaining inductance parameters are comprehensively introduced in this paper. The results of the inductance analytical calculation are verified and evaluated in light of the FEM simulation results and the prototype measurements.

A two-stage based model for partially-buried pile group response in cross-anisotropic saturated media adjacent to moving harmonic loads

The pile foundations are frequently affected by adjacent traffic loads except for general active loads. However, the dynamic responses of the pile groups under moving loads have been rarely reported before. In addition, the influence of material anisotropy is often neglected. In this paper, a three-dimensional (3D) analytical model for the dynamic analysis of partially buried pile groups in stratified saturated cross-anisotropic media under adjacent moving harmonic loadings is developed. Specifically, a 3D Bernoulli–Euler beam theory is adopted to simulate the monopile and then superimposed into the finite element (FE) formulation for the partially embedded pile groups. Subsequently, the basic solutions of layered saturated cross-anisotropic soils are derived by the analytical layer-element approach (ALEA). By combination with ALEA, the two-stage based boundary element (BE) equations for the pile-soil interface are obtained. Finally, by coupling the FE and BE formulations, the dynamical response equation of pile-soil is established. Based on the verification of the accuracy of the proposed methodology by comparisons with existing solutions and FE results from ABAQUS, the impacts of material anisotropy, pile buried length, loading velocity, and pile stiffness on the time-domain dynamic behavior of pile groups are analyzed. The results show that increasing the pile-buried ratio or pile stiffness reduces the magnitude of the dynamic response. Moreover, with the increase of material anisotropic parameters, the peak pile response decreases. And the peak dynamic response first increases and then reduces as the loading velocity increases.

A Critical Discourse Analysis on the Variations of Language Used by Tomboy Characters in Pakistani Dramas

The current study examined the language variations of tomboys' characters in Pakistani dramas to identify the representation of tomboys and the factors that affect their characters by discussing linguistic methods, behaviors of society, stereotypical thinking of society and the role of patriarchy in it. The theoretical underpinning for the current investigation was based on Fairclough's (1989) three-dimensional model for Critical Discourse Analysis. The study employed qualitative research method to investigate the research questions. The data was collected by using a simple random sampling design to collect episodes from two different Pakistani dramas. The tomboys’ characters’ chosen dialogues and the language elements used were divided into three categories based on subjects in the selected episodes. The data was analysed by using the CDA model. leading to conclusions on the role of patriarchy and societal norms in shaping the representation of tomboys in Pakistani dramas. The results of the study showed the negative attitudes of society toward tomboys’ characters. They were often excluded from social groups and activities; discriminated and viewed as less feminine competent. It was concluded that tomboys’ characters could serve as role models for girls who might not conform to traditional gender expectations.

Influence of temperature on wettability of micro hierarchical rough surfaces: A three-dimensional thermodynamic model

Inspired by the micrometer-scale hierarchical microstructures on the surface of cicada wings, this paper presents a three-dimensional thermodynamic analytical model to comprehensively analyze the superhydrophobicity of rough surfaces with micro-hierarchical structures. Emphasis is placed on the variation of normalized free energy and free energy barrier as a function of apparent contact angle for different wettability states. The effect of temperature-dependent intrinsic contact angle on the intertransition between different wettability states is explored. Additionally, the model allows obtaining the equilibrium contact angle and contact angle hysteresis through corresponding calculations. Importantly, the present model elucidates the influence of the height of the micropillar of the paraboloid on the intertransition between different wettability states at a specific temperature. The geometrical parameters of a droplet in a certain environment, when it is in the final stable wettability state, can be designed based on this model. By conducting a thorough investigation into the effect of temperature on the contact angle of rough surfaces with micro-hierarchical structures, this study offers a fresh perspective for understanding the wettability behavior of droplets at the micrometer scale. Moreover, it provides a theoretical basis for designing rough surfaces with micro-hierarchical structures for application in various environments.