3D Model Research Articles

INTELLIGENT INFORMATION TECHNOLOGIES TO SUPPORT DECISION-MAKING WHEN APPLYING THE CAD/CAM/CAE SYSTEM OF DESIGN AND USING ADDITIVE TECHNOLOGIES

The direction of research is the development of principles and methods for making scientifically based decisions in the design and additive manufacturing of bone substitutes based on apatite-biopolymer composites with functional properties depending on the nature of the localization of the cavity bone defect and its size. The relevance is due to the fact that the development of an intelligent decision-making support system based on neural network modeling, the development of methods for their training, tabagato-criterion optimization of design processes, will allow the creation of three-dimensional solid models of defects taking into account their spatial structure and bone substitutes for the synthesis of biomaterials with controlled composition, porosity and mechanical strength, which are optimal for a specific area of bone replacement, which will increase the effectiveness of treatment and prosthetics in orthopedics and traumatology. A set of methods for analyzing images of bone tissue, taking into account its spatial structure, which are obtained by sensors of different physical nature, with the use of neural network models, development of methods of their design, optimization, and training is proposed. A modification of the method of learning neural networks based on gradient descent, based on the application of the theory of nonlinear dynamics, is proposed. Corresponding theoretical provisions have been developed.

Convolutional neural network for assisting accuracy of personalized clavicle bone implant designs

<span lang="EN-US">The clavicle is a long bone that tends to be frequently fractured in the midshaft region. The plate and screw fixing method is mainly applied to address this issue. This study aims to construct a clavicle bone implant design with a consideration to achieve a high accuracy and high-quality surface between the plate and the clavicle surface. The computational tomography scanning (CT-scan) image series data were processed using a convolutional neural network (CNN) to classify the clavicle image. The CNN outcomes were gathered as three-dimensional (3D) volume data of clavicle bone. This 3D model was then proposed for the plate design. The CNN testing results of 97.4% for the image clavicle bones classification, whereas the prints of the 3D model from clavicle bone and its plate and screw design reveal compatibility between the bone surface and the plate surface. Overall, the CNN application to the series of CT images could ease the classification of clavicle bone images that would precisely construct the 3D model of clavicle bone and its suitable clavicle bone plate design. This study could contribute as a guideline for other bone plate areas that need to fit the patient’s bone geometry.</span>

Structure tensor-based Gaussian kernel edge-adaptive depth map refinement with triangular point view in images

<span lang="EN-US">Image reconstruction is the process of restoring the image resolution. In 3D image reconstruction, the objects in different viewpoints are processed with the triangular point view (TPV) method to estimate object geometry structure for 3D model. This work proposes a depth refinement methodology in preserving the geometric structure of objects using the structure tensor method with a Gaussian filter by transforming a series of 2D input images into a 3D model. The computation of depth map errors can be found by comparing the masked area/patch with the distribution of the original image's greyscale levels using the error pixel-based patch extraction algorithm. The presence of errors in the depth estimation could seriously deteriorate the quality of the 3D effect. The depth maps were iteratively refined based on histogram bins number to improve the accuracy of initial depth maps reconstructed from rigid objects. The existing datasets such as the dataset tanks and unit (DTU) and Middlebury datasets, were used to build the model out of the object scene structure. The results of this work have demonstrated that the proposed patch analysis outperformed the existing state of the art models depth refinement methods in terms of accuracy.</span>

Investigating the Accuracy of Boat Propeller Blade Components with Reverse Engineering Approach using Photogrammetry Method

This research aims to investigate the accuracy of 3D scanner by conducting a comparative analysis of AI-based photogrammetry method and Agisoft Metashape software, a more affordable and accessible approach compared to expensive commercial solutions. The proposed method uses photogrammetry and CAD (Computer-Aided Design) to measure propeller blade geometry through a three-stage process. In the first stage, the images are taken with a digital camera with calibrated and encoded targets. Additionally, reconstruct the propeller blades in Geomagic Studio. Taking photos of objects only takes a short time and is professional. Subsequently, in the second stage, the 2D images are processed using Agisoft Metashape software and Artificial Intelligence (AI) algorithms to generate an accurate 3-dimensional (3D) model. The third and final stage employs CAD programs to measure various radii of each blade in the 3D virtual model. To validate the accuracy of the measurements, the results are compared with those obtained through machine CMM measurements of each area on the propeller blade. The results show that this method successfully automates the entire reverse engineering process at low cost, lower shooting time, and producing 3D models with high accuracy. The validation shows that the 3D results using Agisoft Metashape have a smaller error (%) value compared to the 3D results using AI. Ultimately, Agisoft Metashape yields higher accuracy results compared to AI, but the results suggest that AI can serve as an alternative for the reverse engineering process in this modern era.

Prediction and control of profile for silicon steel strip in the whole tandem cold rolling based on PSO-BP algorithm

In the rolling process of silicon steel strip of the five-stand UCMW tandem cold rolling line, the quality of finished profile is the result of cooperative control of five stands, the exit profiles of the first four stands jointly decide the exit profile of the fifth stand, so it is necessary to accurately control the strip profile in the rolling process. However, the shapemeter is only typically equipped at the exit of fifth stand, making it impossible to obtain the strip profile of the first four stands. A profile prediction model for the whole tandem cold rolling based on PSO-BP algorithm is established, compared with the finite element method, this model can satisfy the demand for fast prediction of strip profile and quickly analyzing the profile change characteristics for five stands according to the adjustment of profile control parameters in the industrial field. Firstly, a 3D elastic-plastic finite element model of rolls and strip for five stands is built, and a large number of profile calculation data are as the training sample sets to build the PSO-BP model. Through the transfer calculation of strip profile between adjacent stands, the PSO-BP model of five stands is established, and the validity is verified by comparing with the actual measured data. Secondly, to improve the quality of product profile, focusing on the unreasonable setting of production parameters, many improvement schemes of WRB and WRS for five stands are designed, and the PSO-BP model is used to quickly calculate the strip profile, then comparing the result of each scheme, the optimum improvement scheme is selected, which is furtherly carried out rolling experiments in the industrial field, and the quality of strip profile is well improved. At present, the new scheme has been successfully applied to industrial production.

An innovative dry-lab test rig for mechanical-hydraulic power take-off of wave energy conversion system

A dry-lab test rig is a powerful means to reduce costs in the design process of a wave energy conversion system (WECs). A dry-lab test rig technique allows the use of real components inside a simulation of a mathematical model. This paper presents the development of an innovative dry-lab test rig for the mechanicalhydraulic power take-off (MHPTO) unit of WECs. The development of a drylab test rig of MHPTO involves several processes, such as three-dimension (3D) modelling, component purchasing, structure fabrication, component installation, and operational testing. The developed dry-lab test rig consists of two main parts, such as the simulated wave emulator plant and the real MHPTO unit plant. The simulated wave emulator plant was developed in this test rig to replicate the interaction motion between the ocean wave motion and the wave absorber device. The developed dry-lab test rig was tested using five different irregular wave input conditions to ensure it could perform under the five different wave input conditions. The overall results demonstrate that the developed dry-lab test rig was successfully performed in all sea states. From the results, the profile of electrical power produced by the real MHPTO unit can be clearly obtained in each sea state.

Analysis of mechanical response and failure characteristics of tunnels crossing active faults considering axial force and geometrical nonlinearity

Tunnels subjected to active fault dislocation may experience significant damage. This paper establishes a novel methodology and solution procedure for analyzing the mechanical response and failure characteristics of tunnels subjected to active fault dislocation based on an elastic foundation beam model. The proposed methodology includes axial, transverse, and vertical soil-tunnel interaction terms, in addition to geometrical nonlinearity and axial force terms in the governing equation. This approach has a significantly extended application range, effectively addressing the problems encountered in tunnels crossing active faults with diverse crossing angles, dip angles, and fault types. The proposed methodology is verified by comparison to a 3D FEM model with various fault types, experimental tests, and on-site case, and the results are in excellent quantitative and qualitative agreement with the numerical, experimental, and on-site results. When fault displacement is below 0.5m, disregarding geometric nonlinearity results in calculation errors of approximately 10% to 17% for peak axial force (Nmax), 18% to 22% for peak shear force (Vmax), and 20% to 30% for peak bending moment (Mmax). Finally, the responses caused by different factors, i.e., fault type, fault displacement, tunnel stiffness, and tunnel diameter, are investigated in detail to better understand tunnels crossing active faults. The results show that amongst the various fault types, the Vmax and the Mmax experienced by tunnels subjected to oblique slip-fault dislocation surpass those of other fault types, accompanied by the most extensive failure range. The augmentation of fault displacement, tunnel stiffness, and tunnel diameter precipitates a corresponding escalation in the Nmax, Vmax, Mmax, and failure range. Under oblique-slip fault dislocation, the tunnel undergoes an initial phase of shear failure, followed by tension-bending failure, delineated by distinct fault displacement thresholds of 0.1m and 0.2m, respectively. The proposed methodology provides the advantage of reliable stability analysis and design of tunnels crossing active faults.

Heat-Inducible CAR-T Overcomes Adverse Mechanical Tumor Microenvironment in a 3D Bioprinted Glioblastoma Model

Glioblastoma (GBM) presents a significant therapeutic challenge due to the limited efficacy of existing treatments. Chimeric antigen receptor (CAR) T-cell therapy offers promise, but its potential in solid tumors like GBM is undermined by the physical barrier posed by the extracellular matrix (ECM). To address the inadequacies of traditional 2D cell culture, animal models, and Matrigel-based 3D culture in mimicking the mechanical characteristics of tumor tissues, we employed biomaterials and digital light processing-based 3D bioprinting to fabricate biomimetic tumor models with finely tunable ECM stiffness independent of ECM composition. Our results demonstrated that increased material stiffness markedly impeded CAR-T cell penetration and tumor cell cytotoxicity in GBM models. The 3D bioprinted models enabled us to examine the influence of ECM stiffness on CAR-T cell therapy effectiveness, providing a clinically pertinent evaluation tool for CAR-T cell development in stiff solid tumors. Furthermore, we developed an innovative heat-inducible CAR-T cell therapy, effectively overcoming the challenges posed by the stiff tumor microenvironment.

Formulation, Implementation, and Validation of a 3D Damage-Plasticity Cohesive-Interface Model with Multiple Yield Surfaces for Cyclic Modeling of Mortar Joints

Formulation, Implementation, and Validation of a 3D Damage-Plasticity Cohesive-Interface Model with Multiple Yield Surfaces for Cyclic Modeling of Mortar Joints

3D Hybrid modeling for the ultrasonic phased array inspection of porosity in heavy plates: Simulation and experimental validation

Quantitative NDT modeling and simulation tools are important in design and fabrication of ultrasonic phased array probes with optimum characteristics and reduce the number of experimental efforts and development time. In order to achieve high accuracy (Amplitude deviation < 1 dB) with a low computational time in the simulation, the modeling tools require not only the high-frequency approximation of the ultrasonic wave propagation but also the high-precision electro-acoustic coupling model. This paper describes a computationally efficient 3D time-dependent hybrid model for the simulation of ultrasonic phased array inspection of porosity in heavy plates. This method combines the results of both 3D finite element analysis (PZFLex-FEA) and the semi-analytical ultrasonic simulation “Ray-Tracing”. As a first step, we demonstrate the FEA modeling of an ultrasonic phased array probe, which includes the full 1-3 piezocomposite design with the arrangement of array elements, conducting electrodes, multi-phase backing material, acoustical matching layer and electrical circuit of a 50 Ohm coaxial cable. In the current FEA simulation, we considered the acoustical and electrical cross-talk between the adjacent elements of an ultrasonic array sensor. In the second step, the FEA-simulated ultrasonic pulse-echo signal and its frequency spectrum of an array element in the farfield region are further used as the reference input signal in the CIVA-UT software to simulate the imaging of porosity in heavy plates, quantitatively. The design of the 3D wedge-geometry of the application specific array sensor is modeled and optimized using the CIVA raytracing and multi-phase backing models. The real excitation pulse of the industrial ultrasonic testing equipment “ROMIS (ROSEN Modular Inspection System)” is also included in the simulation to achieve high accuracy in the current hybrid modeling. The dependency of the detectability of the porosity on the frequency of the array sensor and the active element group so-called “Virtual Probe” are quantitatively analyzed. Finally, the 3D hybrid model simulated Time Corrected Gain (TCG) curves of the porosity like defects in the reference steel plates are compared with the real experiments and a good quantitative agreement is achieved.

Research on microplastic deformation of Inconel718 under the conditions of high temperature and high strain rate

The compression experiments of the nickel-based superalloy Inconel718 were carried out with the help of split Hopkinson pressure bar device, and the microstructure evolution law in the compression deformation of the alloy was studied by means of optical microscopy, electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). Based on the dislocation theory, a three-dimensional discrete dislocation dynamics model is established. By simulating the dynamic evolution of the discrete dislocation, the interaction of the dislocation itself and the formation of the dislocation microstructure were captured, and further explore the microplastic deformation process of Inconel718. The results show that deformation conditions significantly affect the rheological behavior and dynamic recrystallization behaviour. The cross slip of dislocations is closely related to temperature and strain rate, which in turn affect the dislocation configuration. The deformation mechanism of Inconel718 under the conditions of high temperature and high strain rate is jointly dominated by dislocation slip and twin deformation. As the temperature increases, the average Schmidt factor increases, and more dislocation slip systems are activated. As the strain rate increases, the number of deformation twins increases, while the thickness of deformation twins decreases.

Pore characteristics and microscopic damage mechanism of disintegrated carbonaceous mudstone exposed to dry-wet cycles

Disintegrated carbonaceous mudstone (DCM), derived from pre-disintegration treatments of waste carbonaceous mudstone, is utilized as filler for highway embankments with the aim of conserving resources. However, the mechanical behavior of DCM is greatly influenced by its microstructure, particularly pore characteristics. The aim of this study is to investigate the pore characteristics and microscopic damage mechanisms of DCM subjected to dry-wet cycles. Triaxial tests, along with microscopic observations using scanning electron microscopy and mercury intrusion porosimetry, were performed. Three-dimensional pore models were reconstructed from the microscopic test results via the Markov chain-Monte Carlo method. Subsequently, a finite element method that accounts for the anisotropy of porosity was proposed based on these pore models. Finally, numerical triaxial tests were performed to analyze stress changes in DCM under triaxial loading using the proposed method. The results show that the shear strength and cohesion of the DCM decrease with an increase in dry-wet cycles, stabilizing notably after four cycles. Meanwhile, the porosity and the number of slender pores in the specimen increase, leading to intricate alterations in pore shape and distribution. A comparison between numerical and laboratory triaxial tests demonstrates closely aligned results, with distinct stress concentration behavior related to porosity anisotropy. It is revealed that dry-wet cycles cause an increase in porosity and the occurrence of more irregular-shaped pores, subsequently leading to a decrease in the cohesion. This microscopic mechanism is responsible for the shear strength damage of DCM.

Managing deepsea oil spills through a systematic modeling approach

Offshore oil exploration and production in deepwater are associated with environmental risks to marine ecosystems. This research introduces DWOSM (Deep Water Oil Spill Model), a three-dimensional Lagrangian model, which is developed to simulate the transport and fate of oil spills resulting from subsea blowouts. DWOSM comprises three interconnected modules: DWOSM-DSD, which predicts the oil droplet size distribution from a blowout release; DWOSM-NearField, simulating plume dynamics and tracking oil droplets within the plume region; and DWOSM-FarField, modeling the evolution of dispersed oil beyond the near-field. Compared to other oil spill models, this integrated approach improves the transition between near and far fields using a near-field particle tracking algorithm. It also employs the thermodynamic models to enable the prediction of oil properties under varying deep water pressure and temperature. To gauge the reliability and efficacy of DWOSM, a hypothetical case situated within a North American context is employed for model testing. The DWOSM and its each module are juxtaposed with other established oil spill models. The outcomes indicate that DWOSM yields comparable results to these models by providing reasonable predictions of a deepwater blowout. The model's verification through case scenario testing and comparison underscores its potential as a decision tool for assessing and managing the potential environmental impacts of offshore petroleum activities.

Computational investigation of transportation and thermal characteristics in a bi-modal slurry flow through a horizontally placed pipe bend

In this study, we develop a three-dimensional computational model to explore the transportation and thermal characteristics of a bi-modal slurry flowing through a horizontally placed 90° pipe bend. The slurry comprises silica sand (SS) and fly ash (FA) granular, with varying combinations (65:35, 75:25, 85:15, 95:05, and 100:0). The computational investigation has been carried out for different carrier fluid's characteristics, including Prandtl number, and flow velocity (5 m/s), for efflux concentrations of Cw = 40–60% for each mixture. Validated with experimental data, the computational approach employs a two-phase Eulerian-Eulerian RNG k-ε turbulence model and the kinetic theory of granular flow. Results reveal that the 65:35 combination exhibits minimal pressure drop, and the 100:0 combination shows maximum heat transfer characteristics, particularly with low-viscosity fluid (Pr = 2.88) and high particle efflux concentration (Cw = 60%). The study also examines bend loss coefficients (Kt), concentration distribution, convective heat transfer coefficient (h), and Nusselt number (Nu) across different Prandtl fluids and efflux concentrations.

Cyclic performance of RC frame joints with drilled openings

The construction industry commonly employs reinforced concrete (RC) beams with utility pipe openings to facilitate the passage of pipes through structures. These openings can be made through pre-construction or post-construction processes. Pre-construction openings in RC members are included in the design, and in most cases, designers include reinforcements around the opening to deal with the stress concentration and failure mechanism caused by the presence of the opening. However, post-construction or drilled openings are added after the structure is built, potentially disrupting established load paths, and developing stress concentrations that are not anticipated by the designer. In this study, three-dimensional nonlinear numerical finite element models (FEM) models were developed and validated according to four sets of experimental data. These models formed the basis for a parametric study exploring different design parameters. Parameters such as the width and depth of the specimen and the size of the opening were investigated. The results suggest that the presence of the opening leads to a brittle behavior and a sudden drop in the strength and stiffness of the specimen after the ultimate load. Increasing the depth of the beam results in more brittle behavior in specimens with openings and decreased the drift ratio where the specimen failed by up to 75%. However, increasing the width of the specimen increases the ductility of these specimens. Finally, opening size was found to lead the specimen to behave more brittle in all cases, and decrease the maximum drift ratio from 5% to 1.5%, and decrease the load capacity in 1.5% drift ratio by up to 61%. This study will help engineers and designers to understand the effect of beam-column joints with post-construction openings under cyclic loading, whether these openings are intentional or by human error.

Urban 3D Modeling as a Precursor of City Information Modeling and Digital Twin for Smart City Era: A Case Study of the Narmak Neighborhood of Tehran City, Iran

Urban 3D Modeling as a Precursor of City Information Modeling and Digital Twin for Smart City Era: A Case Study of the Narmak Neighborhood of Tehran City, Iran

Study of the characteristics of broadband matching antennas for fifth-generation mobile communications based on new composite materials

The presented research aims to analyze in detail the characteristics of broadband matching antennas specifically designed for 5G mobile communications applications, with an emphasis on innovative composite materials. The study focuses on a compact planar loop antenna designed for use on smartphones, covering the LTE/WWAN frequency bands 824 to 960 MHz, 1,710 to 2,690 MHz, and 3,300 to 3,600 MHz for full coverage of modern 5G networks. Experimental and numerical methods are used to broadly analyze the frequency range associated with 5G networks. The features of the use of composite materials in the implementation of antenna devices in 5G technologies are noted. A broadband matching circuit (BMC) with elements with lumped parameters and a reduced sensitivity invariant has been synthesized. A 3D model of the adaptive selective surface controller (SSC) was developed using CST Studio. The study results highlight the benefits of new composite materials in improving the performance of 5G antennas. This research makes a significant contribution to the development of 5G technologies by optimizing antenna design for efficient data transmission in modern mobile networks and can be a valuable resource for engineers and designers working in this field.

A Structure-Based Drug Design Approach for the Identification of Antiviral Compounds Targeting the Chikungunya Virus RdRp Protein

There are an estimated 3 million Chikungunya virus (CHIKV) infections per year, but no vaccines or specific pharmaceutical treatments are available. RNA-dependent RNA polymerase (RdRp) of CHIKV, encoded by nonstructural protein 4 (nsP4), was targeted to identify potential antiviral compounds in this study. A 3D model of the nsP4 was generated by homology modeling technique and Pockdrug-Server was used to predict ligand binding sites. The pharmacophore hypothesis was developed followed by virtual screening. 300 most potential ligands were selected from a library of 3000 compounds, after filtering for the molecules satisfying Lipinski's Rule of Five. Using molecular docking followed by ADMET analysis, 27 leads were then selected. We used MD simulations of the three best compounds that bind to the cataltic, palm, and thumb domains to find out how the ligand-protein interactions change over time. RMSD, RMSF, radius of gyration, free energy landscapes, and principal component analyses revealed that complexes nsP4-ZINC12820763 and nsP4-ZINC33280972 were more stable. Simulated trajectories were further used to compute MMGBSA binding energies of PubChem135638918 (-22.33 kcal/mol), ZINC12820763 (-50.19 kcal/mol) and ZINC33280972 (-32.69 kcal/mol) bound to catalytic, palm and thumb domains, respectively. HOMO and LUMO of potential molecules were also investigated using density functional theory computations. With the support of computational simulations, three compounds were shown to have the potential to inhibit RdRp of CHIKV and need further evaluation using in-vitro and in-vivo analysis.

Exploring Undergraduate Biochemistry Students' Gesture Production Through an Embodied Framework.

Interpreting three-dimensional models of biological macromolecules is a key skill in biochemistry, closely tied to students' visuospatial abilities. As students interact with these models and explain biochemical concepts, they often use gesture to complement verbal descriptions. Here, we utilize an embodied cognition-based approach to characterize undergraduate students' gesture production as they described and interpreted an augmented reality (AR) model of potassium channel structure and function. Our analysis uncovered two emergent patterns of gesture production employed by students, as well as common sets of gestures linked across categories of biochemistry content. Additionally, we present three cases that highlight changes in gesture production following interaction with a 3D AR visualization. Together, these observations highlight the importance of attending to gesture in learner-centered pedagogies in undergraduate biochemistry education.

Conversion of an Entire Image into a 3D Scene with Object Detection and Single 3D Models

Abstract: The paper presents a framework for the extraction of objects from 2D images using object detection techniques in open CV and then generating 3D models of the segmented objects. To achieve precise object detection, the suggested methodology blends deep learning and computer vision methods. The 3D models that are produced have fine-grained geometric and textural features, which improves the object reconstruction's accuracy. The usefulness and robustness of our technique in various settings are demonstrated by experimental findings on a variety of datasets. For use in robotics, virtual reality, and the preservation of cultural heritage, where precise 3D models of actual objects are essential, this research shows great promise.