Large-scale 3D Models Research Articles

Numerical simulation and structural optimization of the diffusion furnace for crystal silicon solar cells

The diffusion furnace is an important device for crystalline silicon solar cell production. Given the rapid evolution of solar cell technology, large-scale, high-efficiency and mass-produced diffusion furnaces are required by the market. This puts forward higher requirements for the diffusion furnaces. In this study, a large-scale 3D model is established and validated by measured data in practical diffusion furnace. Its internal temperature, velocity and gas concentration fields are analyzed. The silicon wafer temperatures are found to be high at the top but low at the bottom. The temperature uniformity at both ends of silicon wafer groups is poor. To solve these problems, three structural optimization methods, namely the inlet pipe optimization, adding uniform-flow plates and the quartz boat optimization, are proposed and analyzed. The average mass fraction in the diffusion furnace is improved by 6.311% using the two-tube forked intake pipe. The uniform flow plates with evenly distributed pores on the lower half effectively improve the gas concentration uniformity on silicon wafer surfaces. The optimized quartz boat can improve the temperature uniformity of silicon wafers, though its deformation slightly increases by 0.338%. The silicon wafer temperature differences after quartz boat optimization are 13.77–50.27% smaller than those before optimization, which are conducive to reducing the thermal stress, the risk of thermal damage and the failure during manufacture and utilization of silicon wafers. Results in this study give guidelines for design and utilization of crystal silicon solar cell diffusion furnaces, some of which have been successfully used in Trina Solar Energy Co., China.

Splitting intensity tomography to image depth-dependent seismic anisotropy patterns beneath the Italian Peninsula and surrounding regions

The region between central Europe and the centre of the Mediterranean is characterised by complex tectonics and kinematics. Here, the interaction between thickened crust, subducting lithosphere and surrounding asthenosphere produces strong and pervasive anisotropy in the upper mantle. Shear wave splitting measurements, the most adopted method to image seismic anisotropy so far, when interpreted in a ray-based framework result in little or no depth resolution, hampering a correct image of the anisotropy distribution with depth. In this study, we aim to better constrain the depth-dependent seismic anisotropy beneath Italy and surrounding regions, by isolating for the first time the source region of anisotropy at different depths. To do that, we perform an anisotropy tomography, adopting the splitting intensity inversion method. It is entirely based on the finite-frequency effect in the splitting of SKS waves. We first computed the splitting intensity using SKS waves recorded at all available permanent and temporary stations over the region, obtaining a huge dataset of measurements used as an input for the tomographic inversion. The large-scale 3D model of seismic anisotropy obtained with the inversion shows a clear change of anisotropy properties in terms of fast polarisation direction and intensity for different depths, thus improving the characterization of the main sources of anisotropy in the mantle as a function of depth. Shallower layers (70–100 km depth) are characterised by a complex and variable oriented pattern of anisotropy fast direction and intensity, which becomes progressively more organised with depth (100–300 km). This pattern suggests a strong control exerted by the geometry and motion of the different slab segments and the large-scale asthenospheric flow generated by subduction and roll-back processes. The strength of anisotropy increases with depth, with high values affecting the bulge of the Alps and Apennines chains and the southern Tyrrhenian subduction system. On the contrary, weaker anisotropy characterises the transition zone from the Apennines to Alpine domains beneath the Po plain, and both the Adriatic and European domains.

Experimental study of hydrodynamics of groundwater flow in karst aquifers

ABSTRACT A large-scale laboratory model is constructed to simulate a karst aquifer. Three groups of experiments are conducted to study the matrix-conduit exchange and how head difference, conduit size, and matrix/conduit gradients affect it. The findings can be summarized as follows; (1) In experiments with higher matrix head, a counterintuitive head inversion, where conduit head becomes higher than matrix head, occurs when the matrix-conduit head difference is small (less than 9.3 cm and 11.5 cm for the 1-inch and 2-inch conduits, respectively); (2) Flow exchange is positively related to rescaled head difference (RSHD), a parameter combining the effect of matrix and conduit gradients and the matrix-conduit head difference; (3) When the conduit has the higher head, the flow exchange is on average 2.8 times higher than when the matrix has the higher head; (4) Doubling the conduit size doubled the flow exchange and increased the length of the head inversion.

Large-Scale 3D Reconstruction from Multi-View Imagery: A Comprehensive Review

Three-dimensional reconstruction is a key technology employed to represent virtual reality in the real world, which is valuable in computer vision. Large-scale 3D models have broad application prospects in the fields of smart cities, navigation, virtual tourism, disaster warning, and search-and-rescue missions. Unfortunately, most image-based studies currently prioritize the speed and accuracy of 3D reconstruction in indoor scenes. While there are some studies that address large-scale scenes, there has been a lack of systematic comprehensive efforts to bring together the advancements made in the field of 3D reconstruction in large-scale scenes. Hence, this paper presents a comprehensive overview of a 3D reconstruction technique that utilizes multi-view imagery from large-scale scenes. In this article, a comprehensive summary and analysis of vision-based 3D reconstruction technology for large-scale scenes are presented. The 3D reconstruction algorithms are extensively categorized into traditional and learning-based methods. Furthermore, these methods can be categorized based on whether the sensor actively illuminates objects with light sources, resulting in two categories: active and passive methods. Two active methods, namely, structured light and laser scanning, are briefly introduced. The focus then shifts to structure from motion (SfM), stereo matching, and multi-view stereo (MVS), encompassing both traditional and learning-based approaches. Additionally, a novel approach of neural-radiance-field-based 3D reconstruction is introduced. The workflow and improvements in large-scale scenes are elaborated upon. Subsequently, some well-known datasets and evaluation metrics for various 3D reconstruction tasks are introduced. Lastly, a summary of the challenges encountered in the application of 3D reconstruction technology in large-scale outdoor scenes is provided, along with predictions for future trends in development.

Multi-UAV Cooperative and Continuous Path Planning for High-Resolution 3D Scene Reconstruction

Unmanned aerial vehicles (UAVs) are extensively employed for urban image captures and the reconstruction of large-scale 3D models due to their affordability and versatility. However, most commercial flight software lack support for the adaptive capture of multi-view images. Furthermore, the limited performance and battery capacity of a single UAV hinder efficient image capturing of large-scale scenes. To address these challenges, this paper presents a novel method for multi-UAV continuous trajectory planning aimed at the image captures and reconstructions of a scene. Our primary contribution lies in the development of a path planning framework rooted in task and search principles. Within this framework, we initially ascertain optimal task locations for capturing images by assessing scene reconstructability, thereby enhancing the overall quality of reconstructions. Furthermore, we curtail energy costs of trajectories by allocating task sequences, characterized by minimal corners and lengths, among multiple UAVs. Ultimately, we integrate considerations of energy costs, safety, and reconstructability into a unified optimization process, facilitating the search for optimal paths for multiple UAVs. Empirical evaluations demonstrate the efficacy of our approach in facilitating collaborative full-scene image captures by multiple UAVs, achieving low energy costs while attaining high-quality 3D reconstructions.

Effect of Ultra-Lightweight High-Ductility Cementitious Composite in Steel–Concrete–Steel (SCS) Plate to Mitigate Ship Slamming Loads

Bottom slamming loads cause considerable local damage to a ship’s body and reduce the ship’s structural performance against harsh sea waves. Although extensive studies have worked on stiffening elements to compensate for local damage due to slamming loads, few studies have concentrated on the ship’s body itself while using new generations of composite plates. Accordingly, a numerical study is conducted to determine the effect of using ultra-lightweight high-ductility cementitious composite in steel–concrete–steel (SCS) composite plate to mitigate bottom slamming loads. A large-scale model of the ship using SCS composite plates is modelled in Abaqus software, and fluid–solid (FSI) interaction is precisely modelled using the Coupled Eulerian–Lagrangian (CEL) method. The results show that using the CEL method with a large-scale 3D model precisely simulates FSI by providing a 6.5% deviation from the experimental result. Moreover, using an SCS plate when considering ultra-lightweight high-ductility cementitious composite results in a considerable reduction (around 95%) in the maximum strain of the ship body and, accordingly, reduces local damage so that, although about 22% of the strain of the outer layer is transferred to the inner part of the ship body containing only steel plate, almost 0% stress transfer is observed for the SCS-based ship’s structure.

플랜트 디지털 트윈 운영을 위한 대용량 모델의 구축 및 표현기술

Although there are many advantages based on the 3D model in the construction of digital twin, an appropriate level of decision is needed, including methods, technologies, manpower, and costs for 3D construction. As a 3D model construction method, there is a design model that can be used or built based on drawings, or reverse modeling method by 3D scanning. And technologies such as data conversion process, model polygon reduction, and 3D object management technology are needed. In the process of construction 3D model in oil, gas, and chemical plants, related technologies were reviewed to efficiently construction large-scale 3D model in digital twin and technologies applied. In the development of a system for operating a large-capacity model, the number of polygons, the number of model objects to be managed, the LOD(level of detail) technology and the number of 3D models to be reduced were studied. These attempts and developments can be utilized to build a new large capacity 3D-based digital twin.

A clipping algorithm for real-scene 3D models

ABSTRACT The development of unmanned aerial vehicle (UAV) oblique photogrammetric technology provides a good foundation for the rapid construction of large-scale and high-definition real-scene 3D models. However, due to the limitations of the modeling process, irrelevant feature data cannot be eliminated in the modeling stage. The built models contain irrelevant features and model distortions caused by errors. At present, most existing clipping algorithms cannot effectively clip real-scene 3D models that are organized as a whole or with levels of detail (LODs). Therefore, this paper proposes a novel algorithm for clipping real-scene 3D models from any perspective based on clipping boundary lines that fit the surfaces of the models. The results of the clipping experiments for 3D models constructed with oblique UAV images show that this algorithm can effectively clip any part of the 3D models, that the clipping results of each level model closely fit the corresponding clipping boundary lines, and that the accuracy of the clipping results is very high. Additionally, the time complexity of the algorithm is O(n 2). In conclusion, the algorithm proposed in this paper provides correct and effective clipping results for real-scene 3D models with LODs that are constructed with photogrammetric or 3D laser scanning data.

Three-dimensional analysis of membrane structures associated with tomato spotted wilt virus infection.

To study viral infection, the direct structural visualization of the viral life cycle consisting of virus attachment, entry, replication, assemblyand transport is essential. Although conventional electron microscopy (EM) has been extremely helpful in the investigation of virus-host cell interactions, three-dimensional (3D) EM not only provides important information at the nanometer resolution, but can also create 3D maps of large volumes, even entire virus-infected cells. Here, we determined the ultrastructural details of tomato spotted wilt virus (TSWV)-infected plant cells using focused ion beam scanning EM (FIB-SEM). The viral morphogenesis and dynamic transformation of paired parallel membranes (PPMs) were analyzed. The endoplasmic reticulum (ER) membrane network consisting of tubules and sheets was related to viral intracellular trafficking and virion storage. Abundant lipid-like bodies, clustering mitochondria, cell membrane tubules, and myelin-like bodies were likely associated with viral infection. Additionally, connecting structures between neighboring cells were found only in infected plant tissues and showed the characteristics of tubular structure. These novel connections that formed continuously in the cell wall or were wrapped by the cell membranes of neighboring cells appeared frequently in the large-scale 3D model, suggesting additional strategies for viral trafficking that were difficult to distinguish using conventional EM.

Refinement of semantic 3D building models by reconstructing underpasses from MLS point clouds

• Refining 3D building models with reconstructed underpasses using MLS point clouds. • Addressing multimodal uncertainties of MLS point clouds and 3D building models. • Comparing MLS point clouds with semantic 3D building models using voxels. • Automatic, CityGML-compliant method of refining LoD2 to LoD3 building models. • CityGML-compliant method of underpass modeling. Semantic 3D building models are provided by public authorities and can be used in applications, such as urban planning, simulations, navigation, and many others. Since large-scale 3D models are typically derived from top-view digital surface models (DSM), they can have detailed roof structures but render planes for façade elements. Furthermore, buildings’ underpasses are often unmodeled, which impacts road space modeling and the building’s volume score. For refining semantic 3D building models, point clouds obtained from mobile laser scanning (MLS) seem to be suitable. In this paper, we present a method of underpass reconstruction by comparing building models’ façades with co-registered MLS measurements. As an alternative approach to from-scratch reconstruction, it exploits existing semantic 3D building models and street-level MLS point clouds to enhance models where required. The method considers the uncertainties of 3D models and measurements in a Bayesian network. Analyzed conflicts between the two representations resulting from ray tracing are used to delineate the underpass’s contours on a façade. Generalized contours are extruded to 3D solid geometries and subtracted from a raw 3D building model, while the semantics is mapped to form an updated semantic 3D building model. The experiments show that the method reaches an accuracy of 12 cm while testing on CityGML LoD2 building models and the open point cloud datasets TUM-MLS-2016 and TUM-FAÇADE representing the Technical University of Munich (TUM) city campus. The validation reveals differences between the reconstructed and updated models in both volumes (up to 18%) and surfaces (up to 20%). Such an extension of road corridors can improve 3D map usage for vehicle navigation and urban simulations.

Pulsed Electromagnetic Sounding of the Bazhenov Formation: High-Performance Computing to Justify a New Geophysical Technology

Abstract —The work is devoted to the theoretical substantiation of a new geophysical technology for studying a unique geological object with unconventional hard-to-recover hydrocarbon reserves. The technology is based on transient electromagnetic sounding from a spatially distributed system of highly deviated wells drilled in target objects near the Bazhenov Formation. The results of computer modeling predetermine a new direction for geological exploration of unconventional hydrocarbon deposits. We consider a numerical solution to the 3D direct problem of pulsed electromagnetic sounding and, on its basis, develop a computational scheme and computer program. A mathematical model is built that describes the sensing process through a pulsed source for electromagnetic field excitation. The Fourier transform is used for time discretization, and the vector finite element method for spatial discretization. This approach makes it possible to obtain many independent 3D problems and effectively solve them in parallel by applying the modern multiprocessor technology. Using the KNL and Broadwell computing nodes of the Siberian Supercomputer Center SB RAS, we performed calculations of electromagnetic signals, which showed a high efficiency of the devised computing scheme and a high performance of the implemented algorithm. Despite the fact that the total peak performance of the KNL nodes is 2.5 times higher than that of the Broadwell nodes, their practical application for performing large-scale 3D modeling on the cluster shows a high efficiency of the latter. When choosing the most suitable computing architecture for the implementation of mass calculations, one should not rely on their formal characteristics only; significant performance is achieved taking into account the peculiarities of the computational methods employed for solving a specific problem. The implemented more efficient ways of performing parallel matrix-vector operations did not significantly increase the performance for this computational scheme. The created computational tools form the basis for further design of the configuration of a pulsed electromagnetic sounding system, and for identifying the capabilities of the new geophysical technology for examining complex geological media.

PANDORA: A Fast, Anchor-Restrained Modelling Protocol for Peptide: MHC Complexes.

Deeper understanding of T-cell-mediated adaptive immune responses is important for the design of cancer immunotherapies and antiviral vaccines against pandemic outbreaks. T-cells are activated when they recognize foreign peptides that are presented on the cell surface by Major Histocompatibility Complexes (MHC), forming peptide:MHC (pMHC) complexes. 3D structures of pMHC complexes provide fundamental insight into T-cell recognition mechanism and aids immunotherapy design. High MHC and peptide diversities necessitate efficient computational modelling to enable whole proteome structural analysis. We developed PANDORA, a generic modelling pipeline for pMHC class I and II (pMHC-I and pMHC-II), and present its performance on pMHC-I here. Given a query, PANDORA searches for structural templates in its extensive database and then applies anchor restraints to the modelling process. This restrained energy minimization ensures one of the fastest pMHC modelling pipelines so far. On a set of 835 pMHC-I complexes over 78 MHC types, PANDORA generated models with a median RMSD of 0.70 Å and achieved a 93% success rate in top 10 models. PANDORA performs competitively with three pMHC-I modelling state-of-the-art approaches and outperforms AlphaFold2 in terms of accuracy while being superior to it in speed. PANDORA is a modularized and user-configurable python package with easy installation. We envision PANDORA to fuel deep learning algorithms with large-scale high-quality 3D models to tackle long-standing immunology challenges.

The forward modeling of 3D gravity and magnetic potential fields in space-wavenumber domains based on an integral method

With the help of the horizontal 2D Fourier transform, 3D convolutions can be transformed into vertical 1D integrations of different wavenumbers. It has already been proven that the Fourier domain method can greatly improve the efficiency of numerical simulations of 3D gravity and magnetic anomalies. Based on the aforementioned strategy, we have developed an efficient 1D integration algorithm in the space-wavenumber domain, which is combined with a fast continuation algorithm along the z-axis for high-efficiency calculations of nonconstant density or magnetization anomalies in rugged terrains. The calculation accuracy and efficiency of four 1D vertical integration methods (i.e., rectangular integrals, quadratic interpolations, Gaussian integrals, and cubic spline interpolations) are compared by using complex models (variable density distribution model and topographic model). The results indicate that, among the four integration methods, the quadratic interpolation method combined with a fast continuation algorithm achieves the best accuracy and efficiency. Compared with other Fourier domain algorithms, the proposed best 1D integration method in space-wavenumber domains achieves good numerical performance in calculating fields on planar and undulating terrains. Moreover, the proposed method is used to calculate the terrain effect on an airborne gravity and magnetic data set for realistic topography modeling. The results indicate that the new algorithm is suitable for the high-efficiency calculation of large-scale complicated 3D models.

3D-GIS Parametric Modelling for Virtual Urban Simulation Using CityEngine

ABSTRACT Modelling and visualization of three-dimensional (3D) models for cities is a great challenge for computer software and graphics. Recently, 3D city modelling has grown due to advances in applications accompanying the information technology revolution. 3D Geographic Information Systems (3D-GIS) have evolved enormously due to the availability of large-scale 3D modelling techniques. These technologies have become very important in representing large cities and conducting various analyses in the city’s virtual environment to support urban decision-making. CityEngine is one of the most recent 3D-GIS modelling applications. CityEngine can be described as parametric modelling using Procedural Modelling (PM) to create 3D urban elements through macros and routines. This paper highlights the importance of 3D Procedural Modelling (PM) of cities in the GIS environment using ESRI CityEngine and presents a parametric concept for designing urban spaces. This issue has been addressed in three respects. First, discuss the concept and strength of parametric design. Second, the concept of procedural modelling and its power to generate complex 3D models using a set of rules is discussed. Finally, CityEngine was evaluated through a real-world case study of a neighbourhood in the new city of Beni-Suef, Egypt. The results confirm the effectiveness of CityEngine as a 3D-GIS modelling software that generates dynamic 3D models from 2D spatial data. While the results are promising, it is important to investigate more complex cases. The CityEngine modelling approach enables comprehensive urban analyses such as sequence vision, façade studies, urban fabric and character, and statistical operations based on attribute database.

Towards Large Parts Manufacturing in Additive Technologies for Aerospace and Automotive applications

Well-established advantages as design freedom, acceleration of design-to-manufacturing cycle, decreased internal logistics reflect on the wider application of Additive Manufacturing as the main manufacturing process. However, its application to large-scale components manufacturing is still an open challenge, because of the limited printing volume available in off-the-shelf machines, slow manufacturing process, and low production volume. After a review of the available contributions, this paper proposes a methodology to handle large-scale 3D models, to be applied before the slicing process. The methodology is based upon the large-scale component subdivision into subparts within CAD environments, using an innovative approach tailored to the problem, and exploits the multi-head capability of collaborative large-scale AM machines. A UAV fixed-wing shows the positive effects in terms of speeding up the manufacturing process. The approach can significantly reduce the printing time of large parts, but a new generation of Additive Manufacturing machines is required to exploit the methodology.

Investigation of Deformation Pattern and Movement Law of the Huge-Thick Conglomerate Stratum by a Large-Scale 3D Model Test with Distributed Optical Fiber Sensor Monitoring.

Mining activities under the circumstances of huge-thick stratum occurrence commonly result in dynamic response of the working face. It is crucial to understand the rock failure and movement of the huge-thick stratum in order to prevent dynamic hazards. This paper introduces distributed optical fiber sensor (DOFS) monitoring into a large-scale model test to investigate the deformation pattern and movement law of the huge-thick conglomerate (HTC); the monitoring results are verified by numerical simulation. The results indicate that DOFS monitoring captures the spatiotemporal evolution of zoning development in the overburden deformation. The deformation field of HTC is illustrated, and there exists a strain basin that can be used to estimate the movement law of HTC. The average strain variability Ex, a new homogenization index for characterizing the overburden deformation, is proposed to describe the broken rules of the HTC. The numerical simulation proves the feasibility of the DOFS monitoring method and the correctness of the deformation pattern and movement law. This study provides efficient methods for DOFS monitoring utilization to investigate mining engineering problems and could be beneficial for unearthing the mechanisms of deep ground rock deformation.

The key technology of large-scale channel reality 3D modeling

The key technology of large-scale channel reality 3D modeling

Lithospheric evolution, thermo-tectonic history and source-rock maturation in the Gippsland Basin, Victoria, southeastern Australia

A fully integrated 3D basin model was built to study the lithospheric structural evolution and the thermal history of the offshore part of the Gippsland Basin to investigate the type, timing and magnitude of its initial opening mechanism and their effects on source rocks. The applied workflow included seismic interpretation of major faults and magmatic features, seismic reinterpretation of existing main stratigraphic boundaries and adjustment of the basement topography. Different scenarios for a McKenzie-type basal heat flow evolution were tested based on a two-step inversion approach, which translates the thickness changes of lithospheric layers into basal heat flow. Finally, a crustal layer model was assigned to the existing 3D numerical basin model and the effects on thermal maturation of petroleum source rocks were investigated. The results of the calibrated inversion model suggest intense lithospheric stretching and mantle upwelling during the Early Cretaceous caused initial breakup and subsidence of the Gippsland Basin. This syn-rift phase was accompanied by increasing basal heat flow from initially ∼50 mW/m2 to a maximum of 80–90 mW/m2. The resulting upwelled Moho with an associated crustal thickness of locally only 8 km agrees with geophysical observations. Elevated paleogeothermal gradients between 50 and 60 °C/km prevailed from ca 120 to 80 Ma. Episodes of compression, uplift, erosion, and thermal subsidence resulted in fast and continuous cooling during the early post-rift and a constant basal heat flow of 45–50 mW/m2 since the Eocene. Two main pulses of petroleum generation were identified in the Paleocene and in the Miocene–Pliocene. This novel two-step crustal layer inversion method allows a detailed reconstruction of the thermal history of rift basins and can provide useful information about the maturation of petroleum source rocks. KEY POINTS A temperature history reconstruction of the Gippsland Basin is given based on a large-scale numerical 3D model. Tectonically induced strong variability in paleoheat flows is recognised. Strong maturation and petroleum generation developed during the Paleogene and Neogene.

Non Rigid 3D Shape Partial Matching Based on Deep Feature Fusion

<p indent=0mm>To meet the requirements of massive and heterogeneous 3D shape partial matching and intelligent retrieval technology, a 3D shape local matching method based on the deep fusion feature of F-PointCNN is proposed. First, the feature bag (BoF) learning model is used to propose an geometric image representation, which can not only effectively distinguish heterogeneous non-rigid 3D models of the same kind, but also reveal the structural similarity of large-scale incomplete 3D models. Next, a cascaded convolutional neural network slearning framework (F-PointCNN) is constructed, where BoF-CNN learns the deep global feature from BoF geometric images and establishes the point feature representation that integrates the local feature and the global feature; Point-CNN refines the point feature and generates deep feature representation which effectively improves the discriminative ability and robustness. Finally, the local shape matching of non rigid 3D model is realized by cross matrix measurement. The open non-rigid 3D shape databases are used to carry out a series of experiments, the results show that the features extracted by proposed method have stronger discriminative ability in large-scale transformation shape classification and higher precision in partial shape matching.

3D mesh simplification with feature preservation based on Whale Optimization Algorithm and Differential Evolution

Large-scale 3D models consume large computing and storage resources. To address this challenging problem, this paper proposes a new method to obtain the optimal simplified 3D mesh models with the minimum approximation error. First, we propose a feature-preservation edge collapse operation to maintain the feature edges, in which the collapsing cost is calculated in a novel way by combining Gauss curvature and Quadratic Error Metrics (QEM). Second, we introduce the edge splitting operation into the mesh simplification process and propose a hybrid ‘undo/redo’ mechanism that combines the edge splitting and edge collapse operation to reduce the number of long and narrow triangles. Third, the proposed ‘undo/redo’ mechanism can also reduce the approximation error; however, it is impossible to manually choose the best operation sequence combination that can result in the minimum approximation error. To solve this problem, we formulate the proposed mesh simplification process as an optimization model, in which the solution space is composed of the possible combinations of operation sequences, and the optimization objective is the minimum of the approximation error. Finally, we propose a novel optimization algorithm, WOA-DE, by replacing the exploration phase of the original Whale Optimization Algorithm (WOA) with the mutate and crossover operations of Differential Evolution (DE) to compute the optimal simplified mesh model more efficiently. We conduct numerous experiments to test the capabilities of the proposed method, and the experimental results show that our method outperforms the previous methods in terms of the geometric feature preservation, triangle quality, and approximation error.