Three-dimensional Reconstruction Research Articles

Three-dimensional pore structure reconstruction and permeability property analysis of carbon paper for proton exchange membrane fuel cells: A computational study

An optimized simulated annealing algorithm was used for the reconstruction three-dimensional pore structure of carbon fiber/polyvinyl alcohol fiber composite paper (CP). The effect of carbon fiber length, carbon fiber percentage, and dispersant amount on the pore structure of CP were first investigated. Then, the seepage simulations were performed leveraging the reconstructed equivalent pore network model for different CP samples. Furthermore, the impact of microscopic pore structure characteristics, including throat radius, coordination number, and pore-throat ratio, on the relative permeability of gas and water phases were quantified. An increase in the length and percentage of carbon fiber resulted in the pores and throats number decreasing, but increasing the average radius of pores and throats. Both throat radius and coordination number demonstrated a positive correlation with the relative permeability of gas and water phase. In contrast, the pore-throat ratio exhibited an inverse relationship with the relative permeability of gas phase, while showcasing a positive association with the relative permeability of water phase. This study provides an important reference for determining the microporous structure of CP and investigating the seepage mechanism.

Left Pulmonary Vein Trunk Length as a Robust Predictor of Long-Term Success of Atrial Fibrillation Catheter Ablation.

Radiofrequency catheter ablation (RFCA) is a commonly used treatment for atrial fibrillation (AF), but the long-term recurrence rate remains relatively high. Given the inconsistent results regarding the role of left pulmonary vein (PV) ostial anatomy in post-ablative recurrence of RFCA in previous studies, we sought to investigate the role of left PV trunk length using an alternative methodology. A total of 369 AF patients undergoing catheter ablation were included. The left/right trunk length (LTL/RTL) of the PV was measured from pre-ablative computed tomography (CT) using three-dimensional reconstruction techniques. We constructed three multivariable Cox models, with the inclusion of the LTL, RTL, and no LTL/RTL, and used the Delong test, integrated discrimination index (IDI), and net reclassification index (NRI) to assess model improvement. We identified optimal cut-off values for LTL with the receiver operating characteristic (ROC) curve, and estimated outcomes using the Kaplan-Meier survival curve. We also used subgroup analysis to evaluate interactions. The results of the Delong test, IDI, and NRI indicated that LTL had a favorable impact on the performance of the multivariate model. Subsequently, the multivariate Cox regression analysis identified LTL as a significant risk factor for post-ablative recurrence of AF (adjusted hazard ratio (HR) = 1.08, 95% CI: 1.05-1.12, p 0.001). According to the ROC curve, the optimal cut-off value for LTL is 11.15 mm, and the Kaplan-Meier estimator revealed different outcomes (p 0.001). We calculated p for interaction between LTL and other factors, and no significant interaction terms were observed. LTL is a robust prognostic indicator for post-ablative outcome in AF patients receiving RFCA, with a longer LTL indicating a higher risk of recurrence.

Unraveling phenotypic heterogeneity in stanford type B aortic dissection patients through machine learning clustering analysis of cardiovascular CT imaging

ObjectiveAortic dissection remains a life-threatening condition necessitating accurate diagnosis and timely intervention. This study aimed to investigate phenotypic heterogeneity in patients with Stanford type B aortic dissection (TBAD) through machine learning clustering analysis of cardiovascular computed tomography (CT) imaging. MethodsElectronic medical records were collected to extract demographic and clinical features of patients with TBAD. Exclusion criteria ensured homogeneity and clinical relevance of the TBAD cohort. Controls were selected on the basis of age, comorbidity status, and imaging availability. Aortic morphological parameters were extracted from CT angiography and subjected to K-means clustering analysis to identify distinct phenotypes. ResultsClustering analysis revealed three phenotypes of patients with TBAD with significant correlations with population characteristics and dissection rates. This pioneering study used CT-based three-dimensional reconstruction to classify high-risk individuals, demonstrating the potential of machine learning in enhancing diagnostic accuracy and personalized treatment strategies. Recent advancements in machine learning have garnered attention in cardiovascular imaging, particularly in aortic dissection research. These studies leverage various imaging modalities to extract valuable features and information from cardiovascular images, paving the way for more personalized interventions. ConclusionThis study provides insights into the phenotypic heterogeneity of patients with TBAD using machine learning clustering analysis of cardiovascular CT imaging. The identified phenotypes exhibit correlations with population characteristics and dissection rates, highlighting the potential of machine learning in risk stratification and personalized management of aortic dissection. Further research in this field holds promise for improving diagnostic accuracy and treatment outcomes in patients with aortic dissection.

Three-Dimensional Reconstruction of Enclosed Environments Based on Two-Dimensional LiDAR: Starting Point and Future Challenges

Three-Dimensional Reconstruction of Enclosed Environments Based on Two-Dimensional LiDAR: Starting Point and Future Challenges

In situ three-dimensional reconstruction and gradient-induced design of ultrastable Zn metal anodes in Zn-Se batteries

Zinc-selenium batteries have high specific and volumetric capacities, but practical development faces key challenge in achieving stable zinc metal anodes, and avoiding zinc dendrite growth, hydrogen evolution reaction (HER) and corrosion. Here, a zinc foam substrate is employed to fabricate three-dimensional gradient electrodes Zn foam@Cu@CuSe2 (ZFCCS) with gradient change of zincophilicity and conductivity. Experimental observations and simulations collectively confirm that the three-dimensional structure and gradient design effectively homogenize interfacial ion flux and diminish local current density. This optimization of the zinc deposition path synergistically fosters high flux and deep deposition of zinc metal while simultaneously preventing dendrite growth. The results demonstrate that the developed ZFCCS electrode produces an excellent Coulombic efficiency of 99.5 % over 1000 plating/stripping cycles, and the corresponding symmetric cell provides an ultra-long dendrite-free cycle life of 800 h at 5 mA cm−2 and 2 mAh cm−2 with a low overpotential of 27.4 mV. In addition, the Zn-Se full cell based on the designed ZFCCS composite anode exerts superior stable cycle life (358.1 mAh g−1 at 2 A g−1 after 1000 cycles). Therefore, the gradient design strategy based on 3D electrodes will be a reference for high performance energy storage devices.

Design of the distribution of iron oxide (Fe3O4) nano-particle drug in realistic cholangiocarcinoma model and the simulation of temperature increase during magnetic induction hyperthermia

The prognosis for Cholangiocarcinoma (CCA) is unfavorable, necessitating the development of new therapeutic approach such as magnetic hyperthermia therapy (MHT) which is induced by magnetic nano-particle (MNPs) drug to bridge the treatment gap. Given the deep location of CCA within the abdominal cavity and proximity to vital organs, accurately predict the individualized treatment effects and safety brought by the distribution of MNPs in tumor will be crucial for the advancement of MHT in CCA. The Mimics software was used in this study to conduct three-dimensional reconstruction of abdominal computed tomography (CT) and magnetic reso-nance imaging images from clinical patients, resulting in the generation of a realistic digital geometric model representing the human biliary tract and its adjacent structures. Subsequently, The COMSOL Multiphysics software was utilized for modeling CCA and calculating the heat transfer law resulting from the multi-regional distribution of MNPs in CCA. The temperature within the central region of irregular CCA measured approximately 46°C, and most areas within the tumor displayed temperatures surpassing 41°C. The temperature of the inner edge of CCA is only 39 ∼ 41℃, however, it can be ameliorated by adjusting the local drug concentration through simulation system. For CCA with diverse morphologies and anatomical locations, the multi-regional distribution patterns of intratumoral MNPs and a slight overlap of drug distribution areas synergistically enhance intratumoral temperature while ensuring treatment safety. The present study highlights the practicality and imperative of incorporating personalized intratumoral MNPs distribution strategy into clinical practice for MHT, which can be achieved through the development of an integrated simulation system which incorporates medical image data and numerical calculations.

Triggering Receptor Expressed on Myeloid Cells 2 Alleviated Sevoflurane-Induced Developmental Neurotoxicity via Microglial Pruning of Dendritic Spines in the CA1 Region of the Hippocampus.

Sevoflurane induces developmental neurotoxicity in mice; however, the underlying mechanisms remain unclear. Triggering receptor expressed on myeloid cells 2 (TREM2) is essential for microglia-mediated synaptic refinement during the early stages of brain development. We explored the effects of TREM2 on dendritic spine pruning during sevoflurane-induced developmental neurotoxicity in mice. Mice were anaesthetized with sevoflurane on postnatal days 6, 8, and 10. Behavioral performance was assessed using the open field test and Morris water maze test. Genetic knockdown of TREM2 and overexpression of TREM2 by stereotaxic injection were used for mechanistic experiments. Western blotting, immunofluorescence, electron microscopy, three-dimensional reconstruction, Golgi staining, and whole-cell patch-clamp recordings were performed. Sevoflurane exposures upregulated the protein expression of TREM2, increased microglia-mediated pruning of dendritic spines, and reduced synaptic multiplicity and excitability of CA1 neurons. TREM2 genetic knockdown significantly decreased dendritic spine pruning, and partially aggravated neuronal morphological abnormalities and cognitive impairments in sevoflurane-treated mice. In contrast, TREM2 overexpression enhanced microglia-mediated pruning of dendritic spines and rescued neuronal morphological abnormalities and cognitive dysfunction. TREM2 exerts a protective role against neurocognitive impairments in mice after neonatal exposures to sevoflurane by enhancing microglia-mediated pruning of dendritic spines in CA1 neurons. This provides a potential therapeutic target in the prevention of sevoflurane-induced developmental neurotoxicity.

Reconstruction method for a three-demensional discrete element numerical model of landslides using an integrated multi-electrode resistivity tomography method and an unmanned aerial vehicle survey

To analyze the hazard-causing modes of landslides, this paper proposes a three-dimensional discrete element model reconstruction method that employs an unmanned aerial vehicle survey and multi-electrode resistivity tomography method. To convert the resistivity profile into a material profile, we adopt the peak of the probability density method for material classification and utilize the Haar wavelet transform for image denoising. Subsequently, inverse distance weighting interpolation and the curtain-point method are used to transform two-dimensional profiles into a 3D visualization model. Similarly, the triangular mesh boundary can be extracted from the 3D visualization model using the curtain-point method. A mapping function f including the macroscopic parameters, was defined to populate the particles within the boundaries. Using the iterative method and defining the loss function L for parameter calibration, the targeted 3D discrete element model was constructed after setting the velocity threshold. This method was applied to the Changhe landslide (September 14, 2019) in Gansu Province, China, which had a typical damaged soil layer due to earthquake and rainfall factors. The results indicate that the lower part first exhibits significant displacement, followed by the upper and middle parts, which is consistent with the on-site inspections and UAV findings.

Multi-factor quality assessment of digital speckle pattern for speckle projection profilometry

Abstract The digital speckle pattern (DSP) is an essential component in the speckle projection profilometry (SPP) task, its quality directly affects the results of three-dimensional (3D) shape reconstruction. However, the SPP field lacks specialized numerical metrics for evaluating speckle quality. To address this issue, this study introduces a multi-factor metric (MFM) for comprehensive DSP assessment. Through comparing the metric, optimal parameter ranges for DSP design and the advisable matching subset size can be determined for SPP algorithm. A global indicator named valid feature distribution (VFD) based on scale-invariant feature transform (SIFT) and Delaunay triangulation, is defined to analyze the overall information distribution in DSPs. In addition, MFM incorporates a local metric called mean subset intensity gradient (MSIG), which aids in selecting the suitable radius for different DSPs to balance the accuracy and efficiency. The quality assessment targets the speckle scene images, allowing for the reverse adjustment of the most suitable DSP according to different scenes. The performance of DSPs can be evaluated based on the accuracy and completeness of 3D reconstruction results. By conducting simulation experiments on the 3ds Max platform, the recommended parameter range for DSP can be inferred, including speckle density ratio, speckle diameter, and random variation rate. Appropriate subset sizes for different scenes are also investigated. Furthermore, the MFM is verified on a real binocular speckle device, demonstrating that the measurement standard deviation of a complex workpiece can be reduced to 0.078 mm using the recommended DSP.

Three-dimensional reconstruction of porous CeO2 single crystal for effective electrolysis of carbon dioxide

In the quest for long-lasting energy alternatives, solid oxide electrolysers have become a crucial technology in facilitating the transformation of CO2 toward fuels and valuable chemicals. This study proposes a unique method for the catalytic reduction of carbon dioxide at the cathode using porous CeO2 single-crystal electrodes in a solid oxide electrolyser, utilizing temperatures from an industrial waste heat stream. The fluxes and chemical states of oxygen-containing species evolved from the cathode were identified and designed, and the catalytic process of CO2 reduction to CO was effectively regulated by the oxygen-containing species (lattice oxygen, oxygen vacancies and adsorbed oxygen). The results show that the CO yield can reach 6.05 mL min−1 cm−1 with porous (111) CeO2 single crystal as the cathode at 850 °C and 1.8 V. The solid oxide electrolyser exhibits remarkable stability even after 100 h of continuous operation.

Advancing Precision Rhinoplasty: Preoperative Digital 3D Surgical Planning.

The aim of the study is to assess the efficacy and advantages of utilizing state-of-the-art three-dimensional (3D) reconstruction technology in preoperative planning for rhinoplasty surgery. It is a study of a single rhinoplasty case that was operated at a tertiary hospital. The patient was assessed through a detailed history, blood investigations, radiological investigations and preoperative 3D (three-dimensional) reconstruction of the face and nose. The study utilized high-resolution CT scans and 3D reconstruction software like 3D (three-dimensional) Slicer and Blender 3D (three-dimensional) to analyze nasal anatomy for preoperative planning in rhinoplasty. External and internal nasal measurements were taken, and axial cross-section analysis was conducted to assess nasal structure deviation. The benefits of 3D (three-dimensional) visualization in surgical planning were evaluated, and surgical management was based on preoperative reconstructions. Comprehensive preoperative evaluations were performed, adhering to ethical guidelines.Preoperative 3D (three-dimensional) reconstruction planning methods facilitated precise surgical planning and execution in rhinoplasty with satisfactory outcomes for both the patient and the surgeon. Incorporating 3D (three-dimensional) reconstruction technology in rhinoplasty preoperative planning enhances surgical precision and patient satisfaction, ensuring optimized surgical outcomes while adhering to ethical standards.

Damage and fracture characteristics of thermal-treated granite subjected to ultra-high pressure jet

The water jet rock breaking technology has broad application prospects in geoenergy development engineering. However, the influence of reservoir temperature on the rock breaking effect is still unclear during the jet rock breaking process. To explore the mechanism of temperature on rock breaking by high-pressure water jets, experiments on the erosion of high-temperature granite by ultra-high pressure pure water jets (UHP-PWJ) and ultra-high pressure abrasive water jet (UHP-AWJ) were conducted at five rock temperatures: 25 °C, 100 °C, 200 °C, 300 °C, and 400 °C. Through three-dimensional reconstruction and microscopic observation techniques, the macroscopic and microscopic characteristics of rock fragmentation were analyzed, ultimately revealing the dynamic damage and rock breaking mechanisms of ultra-high pressure water jet. The results indicated that rock temperature influences result in different fragmentation characteristics under the action of two types of jets, with UHP-PWJ demonstrating significantly superior rock-breaking effects on high-temperature granite compared to UHP-AWJ. As granite temperature increases from 25 °C to 400 °C, the damage depth range for the UHP-PWJ is 30–75 times the nozzle diameter, while for the UHP-AWJ, it is only 30–40 times the nozzle diameter. For UHP-PWJ, the rock breaking mechanism is mainly driven by thermal stress, supplemented by high-speed jet impact. The significant increase in rock temperature significantly enhances its rock breaking effect, with erosion pits appearing in a spindle shape and more complex crack distribution around the pores. Compared with 25 °C granite, the damage caused by 400 °C granite jet impact increased by 6.8 times and the surface area of cracks increased by 6.5 times. For UHP-AWJ, high temperature hard rock fragmentation still relies mainly on jet impact and abrasive grinding. The thermal stress caused by rock temperature has a relatively small impact on its rock breaking effect, and the D value of the internal damage degree of granite at different temperatures is less than 0.005. The erosion pits are conical in shape, and no macroscopic cracks caused by jet impact and thermal cracking can be clearly observed around the pit. The research results can provide a theoretical basis for optimizing the parameters of high-pressure jet development technology for deep geoenergy.

A Segment-Based Algorithm for Grid Junction Corner Detection Used in Stereo Microscope Camera Calibration

Corner detection is responsible for accurate camera calibration, which is an essential task for binocular three-dimensional (3D) reconstruction. In microscopic scenes, binocular 3D reconstruction has significant potential to achieve fast and accurate measurements. However, traditional corner detectors and calibration patterns (checkerboard) performed poorly in microscopic scenes due to the non-uniform illumination and the shallow depth of field of the microscope. In this paper, we present a novel method for detecting grid junction corners based on image segmentation, offering a robust alternative to the traditional checkerboard pattern. Model fitting was utilized to obtain the coordinates at a sub-pixel level. The procedures of the proposed method were elaborated, including image segmentation, corner prediction, and model fitting. The mathematical model was established to describe the grid junction. The experiment was conducted using both synthetic and real data and the experimental result shows that this method achieves high precision and is robust to image blurring, indicating this method is suitable for microscope camera calibration.

Micro-Computed Tomography Analysis and Histological Observation of the Screw-Bone Interface of Novel Porous Scaffold Core Pedicle Screws and Hollow Lateral Hole Pedicle Screws: A Comparative Study in Bama Pigs

Screw loosening is a common complication of pedicle screw internal fixation surgery. This study aimed to investigate whether the application of a porous scaffold structure can increase the contact area between screws and bone tissue by comparing the bone ingrowth and screw-bone interface of porous scaffold core pedicle screws (PSCPSs) and hollow lateral hole pedicle screws (HLHPSs) in the lumbar spine of Bama pigs. Sixteen pedicle screws of both types were implanted into the bilateral pedicles of the L1-4 vertebrae of 2 Bama pigs. All Bama pigs were sacrificed and the lumbar spine was freed into individual vertebrae at 16weeks postoperatively. After the vertebrae were made into screw-centered specimens, micro-computed tomography analysis and histological observation were performed to assess the screw-bone interface and bone growth around and within the screws. We found that the bone condition around PSCPSs and HLHPSs did not show significant differences on micro-computed tomography three-dimensional reconstruction images. CT transverse views showed different bone growth inside the 2 screws. In PSCPSs, bone tissue was seen to fill the internal pores and was evenly distributed around each strut. Inside HLHPSs, bone growth was confined to 1 side of the screw and did not fill the entire cavity. Osteometric analysis showed that bone volume fraction and trabecular number, the parameters representing bone mass, were higher in PSCPSs than in HLHPSs. These differences were not statistically significant (P > 0.05). Histological observations visualized that the osseointegration within PSCPSs was superior to that of HLHPSs, and the tight integration of bone tissue with the porous scaffold resulted in a larger screw-bone integration area in PSCPSs than in HLHPSs. Compared with HLHPSs, PSCPSs possessing a porous scaffold core could promote bone ingrowth and osseointegration, resulting in an effective enhancement of the combined area of the screw-bone interface.

3D Reconstruction of a High-Energy Diffraction Microscopy Sample Using Multi-modal Serial Sectioning with High-Precision EBSD and Surface Profilometry

High-energy diffraction microscopy (HEDM) combined with in situ mechanical testing is a powerful nondestructive technique for tracking the evolving microstructure within polycrystalline materials during deformation. This technique relies on a sophisticated analysis of X-ray diffraction patterns to produce a three-dimensional reconstruction of grains and other microstructural features within the interrogated volume. However, it is known that HEDM can fail to identify certain microstructural features, particularly smaller grains or twinned regions. Characterization of the identical sample volume using high-resolution surface-specific techniques, particularly electron backscatter diffraction (EBSD), can not only provide additional microstructure information about the interrogated volume but also highlight opportunities for improvement of the HEDM reconstruction algorithms. In this study, a sample fabricated from undeformed “low solvus, high refractory” nickel-based superalloy was scanned using HEDM. The volume interrogated by HEDM was then carefully characterized using a combination of surface-specific techniques, including epi-illumination optical microscopy, zero-tilt secondary and backscattered electron imaging, scanning white light interferometry, and high-precision EBSD. Custom data fusion protocols were developed to integrate and align the microstructure maps captured by these surface-specific techniques and HEDM. The raw and processed data from HEDM and serial sectioning have been made available via the Materials Data Facility (MDF) at https://doi.org/10.18126/4y0p-v604 for further investigation.

A Single-Camera-Based Three-Dimensional Velocity Field Measurement Method for Granular Media in Mass Finishing with Deep Learning.

Surface treatment processes such as mass finishing play a crucial role in enhancing the quality of machined parts across industries. However, accurate measurement of the velocity field of granular media in mass finishing presents significant challenges. Existing measurement methods suffer from issues such as complex and expensive equipment, limited to single-point measurements, interference with the flow field, and lack of universality in different scenarios. This study addresses these issues by proposing a single-camera-based method with deep learning to measure the three-dimensional velocity field of granular flow. We constructed a complete measurement system and analyzed the accuracy and performance of the proposed method by comparing the measurement results with those of the traditional DIC algorithm. The results show that the proposed method is very accurate in measuring spatial displacement, with an average error of less than 0.07 mm and a calculation speed that is 1291.67% of the traditional DIC algorithm under the same conditions. Additionally, experiments in a bowl-type vibratory finishing machine demonstrate the feasibility of the proposed method in capturing the three-dimensional flow of granular media. This research not only proposed a novel method for three-dimensional reconstruction and velocity field measurement using a single-color camera, but also demonstrated a way to combine deep learning with traditional optical techniques. It is of great significance to introduce deep learning to improve traditional optical techniques and apply them to practical engineering measurements.

Remnant Pancreas Volume Affects New-Onset Impaired Glucose Homeostasis Secondary to Pancreatic Cancer.

New-onset diabetes (NOD) has been identified as a high-risk factor for the early detection of pancreatic ductal adenocarcinoma (PDAC). The role of tumor volume and remnant pancreas volume (RPV) in the progression from normal to NOD in PDAC patients is not fully illustrated yet. In this cross-sectional study, glycemic metabolism traits of 95 PDAC patients before pancreatic surgery were described and compared with chronic pancreatitis and type 2 diabetes mellitus patients based on the oral glucose tolerance test. The remnant RPV and tumor volume, calculated by three-dimensional reconstruction of radiological images, were included in the ordinal logistic regression models. The prevalence of NOD was high among PDAC patients (38.9%). However, normal glucose tolerance (NGT) or prediabetes mellitus status were present as more than half (24/44) of advanced tumor stage patients. Indexes reflecting beta-cell function but not insulin sensitivity gradually worsened from NGT to NOD patients (all p < 0.05). The remnant pancreas volume (RPV) was identified as a potential protective factor for diabetes secondary to PDAC (odds ratio 0.95, 95% CI [0.92, 0.97], p < 0.001). Reduced RPV causing beta-cell dysfunction might be one of the mechanisms of NOD secondary to PDAC. Subjects with sufficient pancreas volume could not be detected earlier when regarding patients with NOD as the population at risk for PDAC.

Three-Dimensional Reconstruction and Visualization of Underwater Bridge Piers Using Sonar Imaging.

The quality of underwater bridge piers significantly impacts bridge safety and long-term usability. To address limitations in conventional inspection methods, this paper presents a sonar-based technique for the three-dimensional (3D) reconstruction and visualization of underwater bridge piers. Advanced MS1000 scanning sonar is employed to detect and image bridge piers. Automated image preprocessing, including filtering, denoising, binarization, filling, and morphological operations, introduces an enhanced wavelet denoising method to accurately extract the foundation contour coordinates of bridge piers from sonar images. Using these coordinates, along with undamaged pier dimensions and sonar distances, a model-driven approach for a 3D pier reconstruction algorithm is developed. This algorithm leverages multiple sonar data points to reconstruct damaged piers through multiplication. The Visualization Toolkit (VTK) and surface contour methodology are utilized for 3D visualization, enabling interactive manipulation for enhanced observation and analysis. Experimental results indicate a relative error of 13.56% for the hole volume and 10.65% for the spalling volume, demonstrating accurate replication of bridge pier defect volumes by the reconstructed models. Experimental validation confirms the method's accuracy and effectiveness in reconstructing underwater bridge piers in three dimensions, providing robust support for safety assessments and contributing significantly to bridge stability and long-term safety assurance.

Quantitative three-dimensional reconstruction of cellular flame area for spherical hydrogen-air flames

The cellular flame area continues to increase with the development of cells on the spherical flame surface, which will greatly promote the flame burning rate and propagation speed. This work mainly focuses on a new three-dimensional (3D) reconstruction method of the cellular structure on the flame surface, attempting to quantitatively characterize the real flame area. Initially, the visualization investigation of hydrogen-air premixed spherical flames within a constant volume vessel was conducted using the Schlieren optical technique under room temperature and atmospheric pressure conditions. In parallel, the Cellpose 2.0 graphical user interface was used for the preliminary training of the cell segmentation model. Subsequently, this pre-trained model was applied in the image post-processing, enabling the quantitative characteristics extraction of the cellular structure, such as the cells number, area, and the flame radius, etc. Additionally, a concept of peak height h on the flame profile was proposed to characterize the fluctuation degree of flame profile. A new flame equivalent radius ru was defined by the average value of valid distance from flame centroid to flame profile pixel by pixel. Based on the comparison of cell equivalent radius r and average peak height h¯, an innovative 3D reconstruction concept was proposed for the quantitative characterization of flame area. Finally, cellularity factor ξ was introduced to evaluate the cellularization degree on spherical flames surface. Results show that the appearance of secondary cracks marks the formal onset of flame cellularization, accompanied by an increase in the h¯. In the later stages of flame development, cellularization will eventually tend to a stable value of about 0.4, indicating the occurrence of “saturated state”. After 3D reconstruction, the average cell area stable at around 26 mm2 in this stage. The results of this study provide data support for the construction of combustion models in the field of premixed hydrogen-air combustion.

Patient-specific arterial wall generation for intracranial aneurysms with a variable and a near realistic vessel wall thickness for FSI studies

Background and ObjectiveImaging methodologies such as, computed tomography (CT) aid in three-dimensional (3D) reconstruction of patient-specific aneurysms. The radiological data is useful in understanding their location, shape, size, and disease progression. However, there are serious impediments in discerning the blood vessel wall thickness due to limitations in the current imaging modalities. This further restricts the ability to perform high-fidelity fluid structure interaction (FSI) studies for an accurate assessment of rupture risk. FSI studies would require the arterial wall mesh to be generated to determine realistic maximum allowable wall stresses by performing coupled calculations for the hemodynamic forces with the arterial walls. MethodsIn the present study, a novel methodology is developed to geometrically model variable vessel wall thickness for the lumen isosurface extracted from CT scan slices of patient-specific aneurysms based on clinical and histopathological inputs. FSI simulations are carried out with the reconstructed models to assess the importance of near realistic wall thickness model on rupture risk predictions. ResultsDuring surgery, clinicians often observe translucent vessel walls, indicating the presence of thin regions. The need to generate variable vessel wall thickness model, that embodies the wall thickness gradation, is closer to such clinical observations. Hence, corresponding FSI simulations performed can improve clinical outcomes. Considerable differences in the magnitude of instantaneous wall shear stresses and von Mises stresses in the walls of the aneurysm was observed between a uniform wall thickness and a variable wall thickness model. ConclusionIn the present study, a variable vessel wall thickness generation algorithm is implemented. It was shown that, a realistic wall thickness modeling is necessary for an accurate prediction of the shear stresses on the wall as well as von Mises stresses in the wall. FSI simulations are performed to demonstrate the utility of variable wall thickness modeling.