Digital Reconstruction Method Research Articles

Effect of electrolyte level on performance and mass transfer of non-aqueous lithium-oxygen battery

To accurately reveal the effect of electrolyte content on mass transfer within lithium-oxygen batteries and their discharge performance, this study utilizes computed tomography(CT) scanning technology and digital reconstruction methods to construct a geometric model of the lithium-oxygen battery cathode that is equivalent to the actual one. Based on the fundamental principles of mass transfer, fluid dynamics, and electrochemistry, a two-dimensional model for the discharge process of lithium-oxygen batteries is established. This model facilitates analysis of various parameters and their influencing factors, including the distribution of reaction products, pore structure, oxygen concentration distribution, battery performance, and overpotential, within the lithium-oxygen battery cathode. The research findings indicate that the deposition of reaction products alters the cathode structure and material transport; lower discharge current density and higher electrolyte levels are conducive to the dispersed deposition of reaction products, thereby reducing the deposition's resistance to internal mass transfer in the cathode.

Digital image correlation calculation method for RGB-D camera multi-view matching using variable template

Multi-view matching is an indispensable method for digital image correlation 3D reconstruction. However, as the camera viewing angle changes, traditional DIC methods can lead to the accumulation of matching errors and an increase in mismatches, thereby affecting the 3D reconstruction quality. This paper proposes a digital image correlation method for multi-view RGB-D images based on variable template matching. Initial positioning is achieved by dynamically adjusting the size and sampling direction of the variable template. Sub-pixel registration is then performed using the inverse compositional algorithm, followed by multi-view point cloud fusion using the Iterative Closest Point (ICP) registration method. Experimental results show that the iteration speed of point cloud registration is increased by 30%, and the cumulative error is reduced by 62.5%. These improvements demonstrate that the proposed method is suitable for multi-viewpoint matching scenarios, achieving excellent results in multi-view feature point matching and multi-view point cloud fusion, significantly enhancing 3D reconstruction accuracy and efficiency.

Quantitative study of the ossification centers of the body of sphenoid bone in the human fetus

The aim of the present study was to examine the growth dynamics of the two ossification centers of the body of sphenoid bone in the human fetus, based on their linear, planar and volumetric parameters. The examinations were carried out on 37 human fetuses of both sexes aged 18–30 weeks of gestation, which had been preserved in 10% neutral formalin solution. Using CT, digital image analysis software, 3D reconstruction and statistical methods, we evaluated the size of the presphenoid and postsphenoid ossification centers. The presphenoid ossification center grew proportionately in sagittal diameter, projection surface area and volume, and logarithmically in transverse diameter. The postsphenoid ossification center increased logarithmically in sagittal diameter, transverse diameter and projection surface area, while its volumetric growth followed proportionately. The numerical findings of the presphenoid and postsphenoid ossification centers may be considered age-specific reference values of potential relevance in monitoring the normal fetal growth and screening for congenital disorders in the fetus. The obtained results may contribute to a better understanding of the growing fetal skeleton, bringing new numerical information regarding its diagnosis and development.

Three-Dimensional Digitization of Documentation and Perpetual Preservation of Cultural Heritage Buildings at Risk of Liquidation and Loss—The Methodology and Case Study of St Adalbert’s Church in Chicago

This paper presents a three-dimensional (3D) digitization methodology for documenting the appearance and geometry of cultural heritage buildings using modern tools for data acquisition and processing. This work presents a method combining laser scanning of building dimensions with photographic texture acquisition techniques in order to develop accurate, photo-realistic 3D models. This work also presents a method for digital reconstruction of the elements of interiors. This case study presents the process and result of scanning the church of St Adalbert in Chicago along with its inner finishing elements, achieved during the interventional 3D scanning of a historical building interior. The obtained colorized point cloud has 3.5 billion points and a volume of 65 GB. Its creation took nearly 3.5 h on a high-end computer. The generated textured mesh model has 1.6 billion triangles and a volume of 60 GB. The analysis of the results showed that the elements of the church furnishings were reproduced with very high accuracy. The developed 3D model of the interior, appearance and dimensions of the church is its perpetual documentation. It can be used for various purposes, such as popularizing the appearance on the Internet, scientific research on interior artefacts, creating files for VR and shooting high-resolution films.

Quantitative anatomy of the primary ossification center of the squamous part of temporal bone in the human fetus

Detailed numerical data about the development of primary ossification centers in human fetuses may influence both better evaluation and early detection of skeletal dysplasias, which are associated with delayed development and mineralization of ossification centers. To the best of our knowledge, this is the first report in the medical literature to morphometrically analyze the primary ossification center of the squamous part of temporal bone in human fetuses based on computed tomography imaging. The present study offers a precise quantitative foundation for ossification of the squamous part of temporal bone that may contribute to enhanced prenatal care and improved outcomes for fetuses with inherited cranial defects and skeletodysplasias. The examinations were carried out on 37 human fetuses of both sexes (16 males and 21 females) aged 18–30 weeks of gestation, which had been preserved in 10% neutral formalin solution. Using CT, digital image analysis software, 3D reconstruction and statistical methods, the size of the primary ossification center of the squamous part of temporal bone was evaluated. With neither sex nor laterality differences, the best-fit growth patterns for the primary ossification center of the squamous part of temporal bone was modelled by the linear function: y = −0.7270 + 0.7682 × age ± 1.256 for its vertical diameter, and the four-degree polynomial functions: y = 5.434 + 0.000019 × (age)4 ± 1.617 for its sagittal diameter, y = −4.086 + 0.00029 × (age)4 ± 2.230 for its projection surface area and y = −25.213 + 0.0004 × (age)4 ± 3.563 for its volume. The CT-based numerical data and growth patterns of the primary ossification center of the squamous part of temporal bone may serve as age-specific normative intervals of relevance for gynecologists, obstetricians, pediatricians and radiologists during screening ultrasound scans of fetuses. Our findings for the growing primary ossification center of the squamous part of temporal bone may be conducive in daily clinical practice, while ultrasonically monitoring normal fetal growth and screening for inherited cranial faults and skeletodysplasias.

Edge aware depth inference for large-scale aerial building multi-view stereo

Aerial building depth estimation is a crucial task in 3D digital urban reconstruction and learning-based multi-view stereo (MVS) methods have recently shown promising results in this field. However, these methods are mainly developed by modifying the general learning-based MVS framework for aerial depth estimation, which lack consideration about the intrinsic structures of buildings and result in insufficient accuracy. Therefore, we propose an end-to-end edge aware depth inference network for large-scale aerial building multi-views stereo, called EG-MVSNet, which incorporates the building edge information and jointly estimate the depth map and edge map. Firstly, we propose a novel Edge-Sensitive Network based on the differentiable Dynamic Sobel Kernels to obtain reliable building edge features while eliminating other irrelevant features. We further propose an UNet-like Edge Prediction Branch and a Building Edge-Depth Loss to constrain the model focus primarily on the building edge features. Notably, the pseudo ground truth (GT) edge map for each aerial image is obtained with classical gradient operators which do not require additional annotation. Secondly, to incorporate the edge features into the depth prediction module, we introduce an Inter-volume Adaptive Fusion Module that adaptively incorporates the edge features volume into a standard cost volume and guides the regularization of the cost volume. An Edge Depth Refinement Module is further proposed to performs 2D-guidance refinement and avoid over-smoothed or blurred depth boundaries. Extensive experiments on the WHU dataset and LuoJia-MVS dataset show that our model significantly outperforms state-of-the-art performance by more than 22% mean absolute error (MAE) compared to RED-Net and 57% MAE compared to MVSNet. Additionally, to validate our proposed model, we reconstruct a synthetic aerial building benchmark based on WHU dataset. The results as far as correctness and accuracy exceeded the results of other MVS methods in a between-method comparison by at least 12% in MAE metric. The dataset and code can be available at https://github.com/zs670980918/EG-MVSNet.

Multi-particles detection in transformer oil based on lens-free digital holography and transport of intensity equation

Transformer oil quality plays an important role in health condition monitoring of a transformer. In order to better monitor the quality of transformer oil, a hybrid method combining lens-free digital holography and transport of intensity equation is proposed. We take a single-shot hologram of sample oil with a large field of view, and then reconstruct intensity images with different distances, which are necessary inputs of transport of intensity equation. After that, we can get relatively high-resolution image of oil. Via experiments, we compare the results from basic lens-free digital holography reconstruction and hybrid method reconstruction. The results show that, the hybrid method can effectively improve the image reconstruction accuracy and achieve a resolution of 2.67 μm across a large field-of-view of 60.35 mm2, which means that we can get high-resolution zoom-in oil image with more details and quantitative parameters in real time, which is a breakthrough for quick transformer oil testing.

Reconstruction of 3D digital rocks with controllable porosity using CVAE-GAN

Digital rock technology provides an effective approach for analyzing the pore structure and physical properties of rocks in geophysics and petroleum science. Although deep learning techniques have significantly improved the efficiency of digital rock reconstruction, existing works within this field often lack necessary constraints. Therefore, our study proposes a new method for digital rock reconstruction that employs a conditional variational auto-encoder generative adversarial network (CVAE-GAN). This approach integrates the strengths of a conditional variational auto-encoder (CVAE) and a conditional generative adversarial network (CGAN) to produce high-quality digital rocks. To enable the controllable porosity reconstruction of digital rocks, the proposed method includes porosity information within the encoder, decoder, and discriminator. Additionally, we used the Wasserstein GAN with gradient penalty (WGAN-GP) during the training process to enhance the stability of the neural networks. We conducted experimental evaluations using different types of samples to validate the effectiveness of our reconstruction approach. Calculations of pore structure parameters and simulations of rock physical properties were performed on the reconstructed digital rocks, indicating a robust correspondence with both the real samples and theoretical models. These results provide compelling evidence for the accuracy of the proposed method in digital rock reconstruction and suggest its promising prospects for investigating petrophysical properties.

Analysis of reconstructed multisource and multiscale 3-D digital rocks based on the cycle-consistent generative adversarial network method

SUMMARY Digital rock physics (DRP) is important for characterizing the pore characteristics and petrophysical parameters of rocks from a microscopic perspective. Among the digital rock reconstruction methods, the most widely used is the computer tomography (CT) scan method. However, the pore structure of rocks has multiscale features, and CT scan images with a single resolution cannot completely describe the pore structure characteristics of rocks. In this paper, we analysed reconstructed multisource and multiscale 3-D digital rocks based on the cycle-consistent generative adversarial network (CycleGAN) method. This method fully integrates the advantages of the large field of view of low-resolution images and the high-precision features of high-resolution images. To investigate the performance of the method, two sequences of CT scan images of a sandstone (sample A) and a carbonate rock (sample B) collected from oilfields were studied. Moreover, due to the high resolution of scanning electron microscope (SEM) images, we also constructed 3-D digital rocks with different resolutions of the Berea sandstone based on the combination of CT scan images and SEM images. Finally, the statistical properties and absolute permeabilities were calculated to evaluate the accuracies of reconstructed multisource and multiscale 3-D digital rocks. The results show that the reconstructed multiscale digital rocks based on the CycleGAN method have good accuracy in terms of statistical properties and petrophysical properties. Considering the computational cost and computational accuracy, for high- and low-resolution CT scan images and CT scan images with SEM images as training image data sources, we suggest that the resolution of the reconstructed multiscale digital cores is 4–8 times and 4–16 times higher than that of the low-resolution CT scan images, respectively. The findings of our research will be helpful in gaining insight into the petrophysical properties of heterogeneous rocks.

Fractional Fourier-transform filtering and reconstruction in off-axis digital holographic imaging.

An off-axis digital holographic reconstruction method with fractional Fourier transform domain filtering is proposed. The theoretical expression and analysis of the characteristics of fractional-transform-domain filtering are given. It is proven that the filtering in a lower fractional-order transform domain can utilize more high-frequency components than that in a conventional Fourier transform domain under the same size of filtering regions. In simulation and experiment, the results demonstrate that the reconstruction imaging resolution can be improved by filtering in the fractional Fourier transform domain. The presented fractional Fourier transform filtering reconstruction provides a novel (to our knowlede) optional way for off-axis holographic imaging.

Evaluation of the infill design on the tensile properties of metal parts produced by fused filament fabrication

Additive Manufacturing (AM) applications have expanded significantly from rapid prototyping to high-end products such as complex spare parts. AM has enabled advantages of reduced material usage, geometric freedom, and production automation, shaping the future of the manufacturing industries. With the rapid expansion of AM applications, feedstock materials have developed noticeably, from polymers and ceramics to metals and composites. The progress in metal feedstock material discoveries has empowered the exploration of implementing new AM technologies. Fused Filament Fabrication (FFF) is one of the most common and cost-effective material extrusion AM technologies. This study explores the effect of the infill pattern on the tensile mechanical properties of metal parts produced via FFF, using two feedstock materials, 17-PH stainless steel and copper. Two approaches are designed to investigate the results: experimental tensile test, and Finite Element Analysis (FEA) with digital twin reconstruction method. Results show that 17-4 PH Stainless Steel samples with a triangular infill exhibited a 42% drop in ultimate tensile strength compared to solid infill. However, it also revealed a 34% reduction in mass, cost saving of 36%, and a faster fabrication with a 25% reduction in lead time. At the same time, copper samples with triangular infill exhibited a 22% drop in ultimate tensile strength and a 12% mass reduction. However, it revealed a similar lead time with only a 3% reduction. A Scanning Electron Microscope (SEM) was used to investigate the parts’ internal structure and average pore size, to understand the failure mode of the test specimens.

Digital Reconstructions Using Linear Regression: How Well Can It Estimate Missing Shape Data from Small Damaged Areas?

Skeletal remains analyzed by anthropologists, paleontologists and forensic scientists are usually found fragmented or incomplete. Accurate estimations of the original morphologies are a challenge for which several digital reconstruction methods have been proposed. In this study, the accuracy of reconstructing bones based on multiple linear regression (RM) was tested. A total of 150 digital models from complete zygomatics from recent past populations (European and African American) were studied using high-density geometric morphometrics. Some landmarks (i.e., 2, 3 and 6) were coded as missing to simulate incomplete zygomatics and the missing landmarks were estimated with RM. In the zygomatics, this simulated damage affects a few square centimeters or less. Finally, the predicted and original shape data were compared. The results indicate that the predicted landmark coordinates were significantly different from the original ones, although this difference was less than the difference between the original zygomatic and the mean zygomatic in the sample. The performance of the method was affected by the location and the number of missing landmarks, with decreasing accuracy with increasing damaged area. We conclude that RM can accurately estimate the original appearance of the zygomatics when the damage is small.

The investigation of microporous structure and fluid distribution mechanism in tight sandstone gas reservoirs: A case study on the second member of Xujiahe gas reservoirs in Yuanba area

Tight sandstone reservoir is characterized by ultra-low porosity, complex microporous structure and water residues, which shows different gas storage and transport mechanism from conventional reservoirs. Therefore, effective development of tight sandstone gas reservoirs is faced with technical challenges. Microporous structures, distribution mechanism of fluid is a basic issue in gas reservoir evaluation. In this work, we take gas reservoir in the 2nd member of Xujiahe Formation in Yuanba area as an example to analyze the microscopic feature of pore structure and fluid distribution. The three-dimensional digital core has been applied to represent the real microporous structure. Specifically, a digital core reconstruction method based on SEM and casting slice images has been proposed. Ultimately, the mechanism of distribution, mode of occurrence of water residues in tight sandstone reservoirs has been simulated and quantitatively analyzed. The results show that the water residues could been visualized and categorized into three modes, water mass in corner, water film on surface, and water column in throat. The water residues could cause dramatic influence on pore structures, active pore size could be decreased with rising residual water saturation, the magnitude falls by over 50%. In addition, grain size would affect the distribution of water residues, which shows different percentage in medium and fine sand. Pore connectivity is another characteristic factor to describe the microporous structures. In this study, cluster marking algorithm has been applied to obtain the pore connectivity in tight sandstone with different grain size. In medium sand, the pore connectivity is dramatically decreased with rising water saturation, the downward trend become slower when water saturation reaches to 60%. Compared to fine sand, the tendency variation appears when water saturation reaches to 40%. This paper provides an applicable method to reveal the micro-scale reservoir properties and fluid distribution mechanisms in tight sandstone gas reservoirs.

Based on Virtual Reality Technology Research on Innovation and Design of Ceramic Painting Products

In order to obtain the complete color point cloud data of traditional ceramic artworks and reconstruct them efficiently, a 3D digital reconstruction method of ceramic painting products based on virtual reality technology was proposed. By the method, the 3D color point cloud data of ceramic works were collected by the camera 3D scanning equipment. The new postprocessing methods such as fusion and repair were investigated and proposed so as to obtain the complete optimized color point cloud information. The high-fidelity 3D mesh model and simplified mesh of ceramic artworks were obtained through the mesh process and the digital display platform was developed by using virtual reality technology. The experiment results showed that the 3D color point cloud data of traditional ceramic artworks were obtained by +5 exposure blend methods on average in the 6 combined modes and point cloud optimization and repair were completed. High-precision color mesh model was generated and digital promotion and publicity were carried out. The proposed 3D reconstruction technology and virtual display method made a positive exploration for the protection, inheritance, and promotion of China’s ceramic artworks and made a new attempt for the digital protection of cultural heritage by using modern science and technology.

Computational see-through screen camera based on a holographic waveguide device.

This study proposes a novel computational imaging system that integrates a see-through screen (STS) with volume holographic optical elements (vHOEs) and a digital camera unit. Because of the unique features of the vHOE, the STS can function as a holographic waveguide device (HWD) and enable the camera to capture the frontal image when the user gazes at the screen. This system not only provides an innovative solution to a high-quality video communication system by realizing eye-contact but also contributes to other visual applications due to its refined structure. However, there is a dilemma in the proposed imaging system: for a wider field of view, a larger vHOE is necessary. If the size of the vHOE is larger, the light rays from the same object point are diffracted at different Bragg conditions and reflect a different number of times, which causes blurring of the captured image. The system imaging process is analyzed by ray tracing, and a digital image reconstruction method was employed to obtain a clear picture in this study. Optical experiments confirmed the effectiveness of the proposed HWD-STS camera.

New approach for the digital reconstruction of complex mine faults and its application in mining

Visualization of complex geological structures can technically support the accurate prediction and prevention of coal mine disasters. This study proposed a new digital reconstruction method to visualize geological structures based on establishing a virtual model in the digital twin system. This methodology for the digital reconstruction of complex fault structures comprises the following four aspects: (1) collection and fidelity of multi-physical field data of the fault structures, (2) the transmission of multi-physical field data, (3) the normalization of multi-physical field data, and (4) digital model reconstruction of fault structures. The key scientific issues of this methodology to be resolved include in situ fidelity of multi-field data and normalized programming of multi-source data. In addition, according to the geological background and conditions in Da’anshan coal mine in western Beijing, China, a preliminary attempt is made to reconstruct a digital model of fault and fold structures using the methodology proposed in this study.

Digital Reconstruction Method of Power Metering Production Data Based on Digital Twin Technology

With the continuous improvement of the integration and intelligence of ubiquitous power Internet of things system equipment, its cost in life cycle management such as data service, operation monitoring, and safety protection is becoming higher and higher. At the same time, the probability of power grid failure, reduced operation efficiency, and function failure will gradually increase with the development of its scale. Accurately evaluating the metering performance of distribution network digital metering system in the operation of power system and improving its accuracy, stability, and reliability are the key issues for its future use in power trade settlement. In this paper, a digital reconstruction method of power metering production data based on digital twin is proposed. The operation data of power system is collected in real time through the data acquisition module, the operation data is analysed, identified, and predicted, and then the analysis, identification, and prediction results are used to realize the visualization and digitization of operation data. Further, the operation data of the digital metering system are monitored and analysed to verify the effectiveness of the method. The advantages and disadvantages of the design scheme of the digital metering system are obtained by analysing the active power error, which provides the basis of practice and selection for the application of the digital metering system.

Adaptive reconstruction imaging based on K-means clustering in off-axis digital holography

An adaptive filtering method for off-axis digital holographic reconstruction is presented. The spatial spectrum distribution of an off-axis digital hologram is clustered based on the K-means clustering algorithm of unsupervised machine learning . The spatial-spectrum filtering can be carried out by the quantitative comparison of different filtering interception windows. The first-order spectrum including the object information can be automatically located and intercepted after clustering the spatial spectrum distribution of the hologram. The experiment results demonstrate that the reconstruction images with better resolution and imaging quality can be achieved by the adaptive filtering algorithm. This adaptive filtering reconstruction based on K-means clustering provides a new way of automatic reconstruction imaging for off-axis digital holography.

A novel method for multiscale digital core reconstruction based on regional superposition algorithm

To characterize matrix pores and microfractures which are widely developed in unconventional reservoirs and also to analyze flow law in multiscale flow region, some related research has been carried out in this study. Based on the statistical characteristics of microscale and nanoscale scanning images of cores, digital cores of microfractures are reconstructed by an improved Voronoi method and the digital cores of matrix pores are reconstructed by the quartet structure generation set (QSGS). By means of regional superposition algorithm, the digital cores of microfractures are firstly magnified in each divided region and then integrated with the corresponding digital cores of matrix pores. After the superposition is completed in whole regions, numerical model after superposition is reduced to the original size of the digital core of microfractures. Finally, the multiscale digital core is reconstructed. Based on reconstructed multiscale digital core, flow simulation considering the permeability of matrix is carried out by the gray lattice Boltzmann method (GLBM). The results show that by constraining the generation areas of random points, the improved Voronoi method can better reflect the geometric characteristics of specific microfractures and the average relative errors of the two-point function and variation function are 13.36% and 2.52% respectively compared with the original microfractures. The multiscale digital core reconstructed by the regional superposition algorithm integrates the anisotropy of matrix pores while retaining the original characteristics of microfractures. With the increase of permeability of matrix, pressure drop range in the flow simulation region expands, and the average velocity at the outlet of microfractures increases. Compared with the case not considering the permeability of the matrix, the maximum increase of average velocity at the outlet of microfractures can reach 48.37% when the permeability of the matrix is set as 0.75 mD. When the flow direction in the microfractures is transverse, compared with the multiscale digital core with transverse connectivity in the matrix, the multiscale digital core with longitudinal connectivity in the matrix has higher flow velocity at the outlet of microfractures, and the average increase of velocity is up to 1.73%.

Conditional Generative Adversarial Networks for 2D core grayscale image reconstruction from pore parameters

Digital cores are of great significance for reservoir structure simulation, oil and gas exploration and development. Most existing digital core reconstruction methods only generate binary cores with complicated implementation processes, among other problems. To address these problems, this study proposed a combination of core pore parameters and conditional generative adversarial network (CGAN) to realize the 2D reconstruction of core grayscale images from only pore parameters (namely, text-to-image synthesis). The current text-to-image synthesis approaches still have many difficulties in generating fine images, but the technologies of image-to-image generation have improved drastically in recent years. Therefore, the proposed method involves two stages to avoid the difficulty of directly generating core grayscale images from pore parameters. In stage I, we preprocessed core sample images to obtain binary-grayscale image pairs, and then used the CGAN to learn the mapping from core binary images to real sample images. At the same time, the pores in the binary images were segmented and extracted to construct the pore component library. In stage II, on the basis of the given pore parameters, the corresponding pores were randomly extracted from the pore component library to generate binary images, and then the generated binary images were used as input for the trained CGAN model to produce core grayscale images. The experimental results showed that the core grayscale images reconstructed by the proposed method meet the pore conditions and reflect the basic characteristics of real cores. • The reconstruction by our method is based on pore parameters rather than images. • The reconstruction is decomposed into two stages: “pore parameters to binary core” and “binary core to grayscale core”. • The method has a general validity and can reconstruct different types of cores according to the research requirements.