Parametric 3D sleeve modelling based on hybrid dimension

The three-dimensional (3D) morphological structure of wheat directly reflects the interrelationship among genetics, environments, and cropping systems. However, the morphological complexity of wheat limits its rapid and accurate 3D modelling. We have developed a 3D wheat modelling method that is based on the progression from skeletons to mesh models. Firstly, we identified five morphological parameters that describe the 3D leaf features of wheat from amounts of 3D leaf digitizing data at the grain filling stage. The template samples were selected based on the similarity between the input leaf skeleton and leaf templates in the constructed wheat leaf database. The leaf modelling was then performed using the as-rigid-as-possible (ARAP) mesh deformation method. We found that 3D wheat modelling at the individual leaf level, leaf group, and individual plant scales can be achieved. Compared with directly acquiring 3D digitizing data for 3D modelling, it saves 79.9% of the time. The minimum correlation R2 of the extracted morphological leaf parameters between using the measured data and 3D model by this method was 0.91 and the maximum RMSE was 0.03, implying that this method preserves the morphological leaf features. The proposed method provides a strong foundation for further morphological phenotype extraction, functional–structural analysis, and virtual reality applications in wheat plants. Overall, we provide a new 3D modelling method for complex plants.

Restoring-force model for HFC-filled CFS shear walls subjected to in-plane cyclic loading

High-Efficient parametric aeroelastic modeling and experimental validation for a morphing aircraft testbed

3D modelling method and application to a digital campus by fusing point cloud data and image data

Femoral neck anteversion is the torsion of the femoral head with reference to the distal femur. Conventional methods that use cross-sectional computed tomography (CT), magnetic resonance or ultrasound images to estimate femoral anteversion have met with several problems owing to the complex three-dimensional (3D) structure of the femur. A 3D imaging method has been developed that virtually measures femoral anteversion on the 3D computer space with continuous CT slices; this 3D method provides more accurate and reliable results than conventional 2D CT measurements. A 3D modelling method is devised for the measurement of femoral neck anteversion. This method has advantages over the 3D imaging method, such as shorter processing time, reduced number of slices and an objective result compared with the 3D imaging method. The results of the 3D modelling method are compared with the conventional CT methods (2D CT method and 3D imaging method) using 20 dried femurs.

The 3-dimensional (3D) modeling of crop canopies is fundamental for studying functional-structural plant models. Existing studies often fail to capture the structural characteristics of crop canopies, such as organ overlapping and resource competition. To address this issue, we propose a 3D maize modeling method based on computational intelligence. An initial 3D maize canopy is created using the t-distribution method to reflect characteristics of the plant architecture. The subsequent model considers the 3D phytomers of maize as intelligent agents. The aim is to maximize the ratio of sunlit leaf area, and by iteratively modifying the azimuth angle of the 3D phytomers, a 3D maize canopy model that maximizes light resource interception can be constructed. Additionally, the method incorporates a reflective approach to optimize the canopy and utilizes a mesh deformation technique for detecting and responding to leaf collisions within the canopy. Six canopy models of 2 varieties plus 3 planting densities was constructed for validation. The average R2 of the difference in azimuth angle between adjacent leaves is 0.71, with a canopy coverage error range of 7% to 17%. Another 3D maize canopy model constructed using 12 distinct density gradients demonstrates the proportion of leaves perpendicular to the row direction increases along with the density. The proportion of these leaves steadily increased after 9 × 104 plants ha−1. This study presents a 3D modeling method for the maize canopy. It is a beneficial exploration of swarm intelligence on crops and generates a new way for exploring efficient resources utilization of crop canopies.

To investigate the seismic performance of T-stub connected beam-column joints， quasi-static loading tests were conducted on two T-stub joint specimens. Key mechanical indicators， including hysteretic curves， skeleton curves， and failure modes， were obtained. Based on the shape characteristics of the skeleton curves， a simplified skeleton curve model was proposed for this joint type. The mechanical parameter calculation method for the simplified model was established through mechanism analysis and the small deformation superposition principle. By performing regression analysis on experimental data from this study and joint test data from existing literature， the hysteretic rule expression was fitted and the restoring force model for such joints was developed. The validity of the proposed model was verified through a comparative analysis between theoretical calculations and experimental results. Research findings demonstrate that T-stub connected beam-column joints exhibited typical semi-rigid connection behavior with favorable seismic performance. The established restoring force model demonstrated high computational accuracy， making it suitable for seismic performance analysis and evaluation of this type of joint.

In this paper, a 3D human body meshed model with low resolution is obtained by parametric digital human modeling, but the meshed surface is not smooth enough to meet the requirements of practical application. To achieve the smoothing effect of the geometric model of digital human body, this paper proposes a mesh-smoothing method of 3D human model based on Sqrt3 subdivision algorithm. Experiment shows that this method applies to the multicurvature mesh body model based on parametric modeling method and achieves good results. The method is simple, efficient and of well-reserved feature.

This paper proposes an efficient way of modeling 3D faces by using only two — a frontal and a profile — images. Although it is desirable to utilize only one single image for 3D face modeling, more accurate depth information can be obtained if we use a profile face image additionally. Despite this seemly straightforward task, however, no standard solutions for 3D face modeling with two images have yet been reported. To tackle this problem, in our work, we first extract facial shape information from each image and then align these two shapes in order to obtain a sparse 3D face. Then, the observed sparse 3D face is combined into generic dense depth information. By doing so, we reflect both the observed 3D sparse depth information and smooth depth changes around facial areas in our reconstructed 3D shape. Finally, the intensity of the frontal image is texture-mapped onto the reconstructed 3D shape for realistic 3D modeling. Unlike other 3D modeling methods, our proposed work is extremely fast (within a few seconds) and does not require any complex hardware settings or calibration. We illustrate our 3D modeling results by using the MPIE-database and demonstrate the effectiveness of the proposed approach.

Skeletal evidence dating back to the Mesolithic period is scarce and should be studied under a multidisciplinary perspective. The primary objective of the study was to carefully assess the skeleton of a young woman from this era, named “Avgi,” to compile its bioarchaeological profile, analyze its paleopathology and dental pathology, and deploy a 3D reconstruction and modeling method in order to reveal her face. Both demographic and pathological information were drawn from macroscopically observing the bones, long bone X-rays, skull CT and X-rays, 3D modeling and printing of the skull, and panoramic dental X-rays. The Manchester method was used for the 3D facial reconstruction. On analysis, we determined that Avgi was a female adolescent, aged around 17–19 years at death, and likely suffering from iron deficiency anemia and Class III dental malocclusion. Notably, Harris lines and a hair-on-end pattern were identified in the long bones and skull radiographs, respectively. Various less significant skeletal lesions reflected potential minor pathologies. Our findings suggest that multidisciplinary collaborative approaches should be followed in the modern study of lesser-known past eras. Multiple scientific perspectives, as well as social structures, geographical aspects, settlements, population movements, and social networks should all be taken into account when assessing lifestyle characteristics and paleopathological signs in skeletal remains.

Simplified models are widely applied in finite element computations regarding mechanical and structural problems. However, the simplified model sometimes causes many deviations in the finite element analysis (FEA) of structures, especially in the non-designed structures which have undergone unknowable deformation features. Hence, a novel FEA methodology based on the parametric model by approximating three-dimensional (3D) feature data is proposed to solve this problem in the present manuscript. Many significant and effective technologies have been developed to detect 3D feature information accurately, e.g., terrestrial laser scanning (TLS), digital photogrammetry, and radar technology. In this manuscript, the parametric FEA model combines 3D point clouds from TLS and the parametric surface approximation method to generate 3D surfaces and models accurately. TLS is a popular measurement method for reliable 3D point clouds acquisition and monitoring deformations of structures with high accuracy and precision. The B-spline method is applied to approximate the measured point clouds data automatically and generate a parametric description of the structure accurately. The final target is to reduce the effects of the model description and deviations of the FEA. Both static and dynamic computations regarding a composite structure are carried out by comparing the parametric and general simplified models. The comparison of the deformation and equivalent stress of future behaviors are reflected by different models. Results indicate that the parametric model based on the TLS data is superior in the finite element computation. Therefore, it is of great significance to apply the parametric model in the FEA to compute and predict the future behavior of the structures with unknowable deformations in engineering accurately.

To investigate the seismic behaviors of novel steel-reinforced concrete composite frames prestressed with bonding tendons (PSRCFs), 15 groups of PSRCF specimens were designed with the following main parameters: the cubic compressive strength of high-strength concrete (fcu), the axial compression ratio of frame columns (n), the slenderness ratio of frame columns (β), the steel ratio of angle steel (α), the span–height ratio of frame beams (L/hb), and the prestressing degree (λ). Based on the modified concrete constitutive model proposed by Mander and the prestressing effect applied by the cooling method, the finite element models of PSRCFs were established by using ABAQUS software, the static analysis on the frame structures under the combined actions of axial forces and horizontal loads was carried out, and the monotonic load–displacement curves were explored. By comparing with the skeleton curves obtained by the experimental hysteretic curves, the rationality of the modeling method was verified. The PSRCFs had good mechanisms of strong columns and weak beams. Based on this, the influences of different parameters on the seismic behaviors such as hysteretic curves, skeleton curves, stiffness degradations, energy dissipation capacities, and ductility of the specimens were investigated. The results show that the hysteretic curves of the PSRCFs are full and have no pinch phenomenon. The ultimate load and the stiffness degradation of specimens can be improved significantly by increasing α, and on the contrary, the ultimate load and stiffness degradation decreased by increasing β. The ductility of the specimens decreased gradually with the increasing β and n. The energy dissipation capacity of the specimens decreased with the increasing β. The trilinear model of the skeleton curves and the restoring force model of PSRCFS were established by statistical regression, which agree well with the numerically simulated results. These can provide theoretical support for the elastoplastic analysis on this kind of PSRCF structure.

This article studies the application of nonparametric modeling approach to model magnetorheological (MR) dampers. For comparison purposes, another typical parametric modeling method for electrorheological (ER) and MR dampers is reviewed. The existing parametric MR damper model includes a stiff Bouc-Wen model that is not friendly for simulation study and real time implementation of model-based advanced control algorithms. In order to avoid the difficulties by using the existing parametric model, the test data from a commercialized MR damper is employed to develop nonparametric models, which can consist of a series of numerically efficient mathematic functions. In addition, the selected functions are required to be continuous and differentiable for potential model-based control algorithms. The results of the nonparametric models show that such different models are comparable. Furthermore, one nonparametric model is selected to be compared with a parametric model and the test data to illustrate the accuracy of the model. The comparison shows that the proposed nonparametric models are able to accurately predict the damper force characteristics, damper bilinear behavior, hysteresis, and electromagnetic saturation. It is further shown that the nonparametric models can be numerically solved with an integration step size of the order of 10 2 s, much faster than the parametric models of the order of 10 5 s, which clearly shows that the proposed nonparametric models are feasible even for real time model-based control algorithms.

In this study, the use of the three-dimensional modeling method was tested in taking some body measurements in camels with a practical method and was compared with other measurement methods. As the animal material of the study, 12 single-humped dromedary female camels and 14 double-humped Camelus dromedarius × Camelus bactrianus: F1 male camels, a total of 26 camels, were used in three camel farms in Incirliova district of Aydın province. The body measurements are taken from each animal by using different three methods, namely by the manual method (MM), by the photography method (PM), and by the three-dimensional modeling method (3D) were the withers height (WH), the back height (BH), the rump height (RH), the body length (BL), the brisket height (BRH), the abdominal height (AH), the shoulder width (SW), and the rump width (RW), and these values were compared with each other. As a result of this study, the mean values of MM and 3D measurement values were very close to each other and the difference between them was found to be statistically insignificant (P < 0.05). The difference between the means of PM and MM/3D measurement values was found to be significant (P < 0.05). In the measurements taken by MM, 3D, and PM methods in male camels, the values obtained by MM and 3D methods for WH, BH, RH, BRH, AH, BL, and SW were very close to each other and the differences between them were found insignificant statistically (p < 0.05). On the determined regression graph, a linear was found between MM and 3D measurement values. As a result of this study, it has been determined that the 3D modeling method can be used as a remote and more practical method in determining the morphological features of large-scale animals such as camels more reliably, more easily, and more practically.

The modeling method of hydraulic fracturing fracture network combined with microseismic monitoring is currently a hot research topic. In the process of hydraulic fracturing production, previous studies have established a fracture model after fracturing based on the recorded source coordinates, earthquake time, and moment magnitude throughout the entire fracturing cycle, in order to evaluate the fracturing results. However, in the process of reservoir fracturing transformation, real-time evaluation of fracturing effect and provision of fracturing guidance are required. The method of establishing fracture models through long-term data collection is obviously not applicable. Nevertheless, existing research lacks efficient and direct 3D fracture network modeling methods based on microseismic events. To address these challenges, this study introduces a novel three-dimensional fracture network model reconstruction process, DEFME (Dimensionality Enhancement and Fracture Modeling of Microseismic Event Location Information), specifically tailored for datasets containing only the source coordinate information of microseismic events. This innovative process initially incorporates the improved DB-RANSAC (Density-Based Random Sample Consensus) method, introducing new regional microseismic event normal vector constraint information. It transforms the conventional DBSCAN(Density-Based Spatial Clustering of Applications with Noise) clustering algorithm into the NC-DBSCAN (Normal Vector Constraint-DBSCAN) method, combining normal vector constraints with density constraints for microseismic event point clustering. Finally, the Alpha-shape method is employed to extract contour information for each fracture, constructing a three-dimensional plane geometric model of the fracture. To validate the efficacy of the proposed processing workflow, synthetic data and public dataset are utilized. The corresponding results indicate that DEFME has successfully overcome noise interference and efficiently and accurately established a three-dimensional fracture network model based on microseismic events.