Shape Model Research Articles

A Generative Shape Compositional Framework to Synthesize Populations of Virtual Chimeras.

Generating virtual organ populations that capture sufficient variability while remaining plausible is essential to conduct in silico trials (ISTs) of medical devices. However, not all anatomical shapes of interest are always available for each individual in a population. The imaging examinations and modalities used can vary between subjects depending on their individualized clinical pathways. Different imaging modalities may have various fields of view and are sensitive to signals from other tissues/organs, or both. Hence, missing/partially overlapping anatomical information is often available across individuals. We introduce a generative shape model for multipart anatomical structures, learnable from sets of unpaired datasets, i.e., where each substructure in the shape assembly comes from datasets with missing or partially overlapping substructures from disjoint subjects of the same population. The proposed generative model can synthesize complete multipart shape assemblies coined virtual chimeras (VCs). We applied this framework to build VCs from databases of whole-heart shape assemblies that each contribute samples for heart substructures. Specifically, we propose a graph neural network-based generative shape compositional framework, which comprises two components, a part-aware generative shape model that captures the variability in shape observed for each structure of interest in the training population and a spatial composition network that assembles/composes the structures synthesized by the former into multipart shape assemblies (i.e., VCs). We also propose a novel self-supervised learning scheme that enables the spatial composition network to be trained with partially overlapping data and weak labels. We trained and validated our approach using shapes of cardiac structures derived from cardiac magnetic resonance (MR) images in the UK Biobank (UKBB). When trained with complete and partially overlapping data, our approach significantly outperforms a principal component analysis (PCA)-based shape model (trained with complete data) in terms of generalizability and specificity. This demonstrates the superiority of the proposed method, as the synthesized cardiac virtual populations are more plausible and capture a greater degree of shape variability than those generated by the PCA-based shape model.

SCorP: Statistics-Informed Dense Correspondence Prediction Directly from Unsegmented Medical Images.

Statistical shape modeling (SSM) is a powerful computational framework for quantifying and analyzing the geometric variability of anatomical structures, facilitating advancements in medical research, diagnostics, and treatment planning. Traditional methods for shape modeling from imaging data demand significant manual and computational resources. Additionally, these methods necessitate repeating the entire modeling pipeline to derive shape descriptors (e.g., surface-based point correspondences) for new data. While deep learning approaches have shown promise in streamlining the construction of SSMs on new data, they still rely on traditional techniques to supervise the training of the deep networks. Moreover, the predominant linearity assumption of traditional approaches restricts their efficacy, a limitation also inherited by deep learning models trained using optimized/established correspondences. Consequently, representing complex anatomies becomes challenging. To address these limitations, we introduce SCorP, a novel framework capable of predicting surface-based correspondences directly from unsegmented images. By leveraging the shape prior learned directly from surface meshes in an unsupervised manner, the proposed model eliminates the need for an optimized shape model for training supervision. The strong shape prior acts as a teacher and regularizes the feature learning of the student network to guide it in learning image-based features that are predictive of surface correspondences. The proposed model streamlines the training and inference phases by removing the supervision for the correspondence prediction task while alleviating the linearity assumption. Experiments on the LGE MRI left atrium dataset and Abdomen CT-1K liver datasets demonstrate that the proposed technique enhances the accuracy and robustness of image-driven SSM, providing a compelling alternative to current fully supervised methods.

ShapeMed-Knee: A Dataset and Neural Shape Model Benchmark for Modeling 3D Femurs.

Analyzing anatomic shapes of tissues and organs is pivotal for accurate disease diagnostics and clinical decision-making. One prominent disease that depends on anatomic shape analysis is osteoarthritis, which affects 30 million Americans. To advance osteoarthritis diagnostics and prognostics, we introduce ShapeMed-Knee, a 3D shape dataset with 9,376 high-resolution, medical-imaging-based 3D shapes of both femur bone and cartilage. Besides data, ShapeMed-Knee includes two benchmarks for assessing reconstruction accuracy and five clinical prediction tasks that assess the utility of learned shape representations. Leveraging ShapeMed-Knee, we develop and evaluate a novel hybrid explicit-implicit neural shape model which achieves up to 40% better reconstruction accuracy than a statistical shape model and implicit neural shape model. Our hybrid models achieve state-of-the-art performance for preserving cartilage biomarkers; they're also the first models to successfully predict localized structural features of osteoarthritis, outperforming shape models and convolutional neural networks applied to raw magnetic resonance images and segmentations. The ShapeMed-Knee dataset provides medical evaluations to reconstruct multiple anatomic surfaces and embed meaningful disease-specific information. ShapeMed-Knee reduces barriers to applying 3D modeling in medicine, and our benchmarks highlight that advancements in 3D modeling can enhance the diagnosis and risk stratification for complex diseases. The dataset, code, and benchmarks will be made freely accessible.

Shape of contact between deformable material and elastic rollers

The study is devoted to the analysis of the contact shape in a symmetrical roll module for the case when changes in the thickness of the material and the roller coating at each point of the contact zone occur in the vertical direction of the strip of material. A mathematical model of the shape of contact between a deformable material and elastic rollers is developed. Particular types of mathematical models of the contact shape are obtained in cases where the material being processed is absolutely elastic, elasticviscous, and plastic. It was revealed that the shape of the contact depends primarily on the geometric and deformation properties of the strip of material being processed and the roller coating, and the deformation rate.

Statistical Analysis of Complex Shape Graphs.

This paper provides developments in statistical shape analysis of shape graphs, and demonstrates them using such complex objects as Retinal Blood Vessel (RBV) networks and neurons. The shape graphs are represented by sets of nodes and edges (articulated curves) connecting some nodes. The goals are to utilize nodes (locations, connectivity) and edges (edge weights and shapes) to: (1) characterize shapes, (2) quantify shape differences, and (3) model statistical variability. We develop a mathematical representation, elastic Riemannian metrics, and associated tools for shape graphs. Specifically, we derive tools for shape graph registration, geodesics, statistical summaries, shape modeling, and shape synthesis. Geodesics are convenient for visualizing optimal deformations, and PCA helps in dimension reduction and statistical modeling. One key challenge in comparing shape graphs with vastly different complexities (in number of nodes and edges). This paper introduces a novel multi-scale representation to handle this challenge. Using the notions of (1) "effective resistance" to cluster nodes and (2) elastic shape averaging of edge curves, it reduces graph complexity while retaining overall structures. This allows shape comparisons by bringing graphs to similar complexities. We demonstrate these ideas on 2D RBV networks from the STARE and DRIVE databases and 3D neurons from the NeuroMorpho database.

Study on deconvolution of alpha-particle spectra using metaheuristic optimization and multivariate analysis

To find a global optimal solution and obtain further insight into the parameters of the peak shape fitting function, metaheuristic optimization algorithms, and multivariate analysis techniques are employed to study the deconvolution of alpha-particle spectra. An improved peak shape model composed of the Bortels-Collaers function and Lévy distribution function, which aims to handle the high-energy tailing, is proposed. A newly developed metaheuristic optimization method, Bonobo Optimizer (BO) is adopted to seek optimal parameters in the peak shape function. Multivariate analysis (MVA) techniques are used to find hidden information in the shape model. Pearson's correlation tells the mutual variation relationship among parameters, while Multidimensional scaling (MDS) shows similarities of parameters through a 2D plot. Effects of parameters upon the regression accuracy are obtained via the Student t-test. Self-organizing Mapping (SOM) is utilized to mine intrinsic relations among these parameters through visual images. AM243-1 test alpha spectra example is selected to examine the proposed methodology. The improved model is more accurate when handling the high-energy tailing features. Compared with traditional gradient-based optimization algorithms, BO can find global solutions without tedious work in initial solution setting and constraint handling. More information is mined through MVA and further understanding of the peak shape function is obtained.

Direct Solid Modelling in Virtual Reality for Systems Architecting

Virtual reality (VR) is gaining more and more interest in multidisciplinary early design activities, from eliciting stakeholder needs to designing a system architecture. The design of a system architecture can be simplified as the definition of three views: functional, behavioural, and structural. The geometric modelling capabilities needed for the embodiment design are still based on desktop-based parametric CAD models, which were eventually transformed into a polyhedral model that can be visualised in VR. When a multidisciplinary team gets together to generate candidate design architecture, they need to create conceptual 3D shapes and determine the layout of components. In this paper, we propose the Virtual Reality Shape Modelling (VRSM) environment for the immersive direct modelling of 3D shapes in VR. VRSM integrates the open-source FreeCAD shape modeller with the game engine Unity. FreeCAD enables the user to capture the history of feature-based operations and to create a parametric representation needed for detailed CAD activities, whereas Unity allows the interaction with polyhedral models in a 3D environment. The current version of VRSM offers modelling capabilities to create, delete, move and resize canonical shapes and apply Boolean operators on a polyhedral model in VR. At the same time, the parametric definition in FreeCAD evolves synchronously.

Fast and Simple Statistical Shape Analysis of Pregnant Women Using Radial Deformation of a Cylindrical Template.

Non-rigid deformation of a template to fit 3D scans of human subjects is widely used to develop statistical models of 3D human shapes and poses. Complex optimization problems must be solved to use these models to parameterize scans of pregnant women, thus limiting their use in antenatal point-of-care tools in low-resource settings. Moreover, these models were developed using datasets that did not contain any 3D scans of pregnant women. In this study, we developed a statistical shape model of the torso of pregnant women at greater than 36 weeks of gestation using fast and simple vertex-based deformation of a cylindrical template constrained along the radial direction. The 3D scans were pre-processed to remove noisy outlier points and segment the torso based on anatomical landmarks. A cylindrical template mesh was then fitted onto the segmented scan of the torso by moving each vertex of in the direction of the radial vector. This process is computationally inexpensive taking only 14.80 seconds to deform a template with 9090 vertices. Principal component analysis (PCA) was performed on the deformed vertex co-ordinates to find the directions of maximum variance. The first 10 principal vectors of our model explained 79.03% of the total variance and reconstructed unseen scans with a mean error of 2.43 cm. We also used the PCA weights of the first 10 principal vectors to accurately predict anthropometric measurements of the pregnant women.

Effect of specimen thickness on fatigue crack shape evolution for aluminum alloy

The investigation of fatigue crack propagation and fracture mechanisms in high-thickness metal plates holds pivotal importance in the advancement of a three-dimensional damage tolerance assessment methodology. This research also bears significant implications for ensuring the safe operation of large-scale mechanical equipment. In this study, we examine the influence of specimen thickness on the evolution of fatigue crack shapes in an aluminum alloy. Fatigue crack growth tests were conducted on single-edge notch tension specimens to explore the impact of specimen thickness on the shape of fatigue crack growth. Additionally, we propose a calculation model for crack growth shape based on an energy model in this paper. Both experimental and analytical findings indicate that specimen thickness does indeed exert an influence on fatigue crack shape. Specifically, as the specimen thickness increases, the crack shape transitions from resembling a “fingernail” to a “saddle” shape.

Automatic characterization of Meibomian gland morphology

Aims/Purpose: To characterize the Meibomian gland (MG) morphology in healthy subjects with an automatic software.Methods: An automatic software was developed for image analysis in R code, consisting of 4 stages: (1) selection of the region of interest, (2) image preprocessing to obtain a binary and a skeleton image, (3) modelling of each MG to fit each MG to a piecewise linear model, and (4) quantification of the following MG features: tortuosity, MG shortening, number of MGs, deviation from a vertical line, and MG area. Meibography images of the upper eyelid were acquired using the Easy Tear View+®. A group of 156 healthy subjects were included, with a mean age and confidence interval (CI) of 43.88 (95% CI: 41.38–46.37) years, range 16–76 years. Reference intervals (RI) were calculated for each MG feature to be used as a diagnostic tool to classify a specific value as normal or non‐normal. Generalized Additive Models for Location, Scale and Shape were used to estimate the percentile curve for each morphologic feature of MG, considering the influence of age and sex.Results: Age had an influence on tortuosity, mean = 0.3 (95% CI: 0.3–0.31), RI: 0.19–0.4 <20 years, and 0.24–0.39 at 50–60 years. Age and sex had an influence in the MG shortening, mean = 63% (95% CI: 62–64%), mean RI: 58–74% <20 years; 59–84% >75 years; women RI: 56–71% <20 years; 57–82% >75 years. The rest of the variables were not affected by age or sex: number of MGs = 16.05 (95% CI: 15.28–16.82), RI: 8–27; vertical deviation = 0.37 (95% CI: 0.36–0.38), RI: 0.29–0.45, and MG area = 14% (95% CI: 14–15%), RI: 8.17–19.81%.Conclusions: Tortuosity variability decreases between 45 and 60 years of age. The MG shortening increases with age and is higher in men. These values could be useful to classify a meibography image as normal or non‐normal, helping to diagnose MG alterations in an objective way.

'Age specific variations in ovarian reserves in healthy fertile and infertile women: A cross sectional study.

Ovarian reserve tests are valuable for evaluation of female fertility, and to formulate appropriate treatment strategies for infertile women. Antral follicle count (AFC) and Anti-Mullerian hormone (AMH) are most reliable markers of ovarian reserve which are related inversely to age. There are many factors that affect ovarian reserve like race, ethnicity, fertility status, BMI or any chronic illness. We conducted this study to find outage specific nomograms for AMH and AFC among fertile and Infertile Indian women, to find out any variations between fertile and Infertile ovarian reserves at various centiles, to define the age cut-off of decline in AMH and AFC among fertile and Infertile Indian women and to find correlation between AMH and AFC. It was a prospective cross sectional single centre study conducted at a tertiary hospital of northern India from March 2017 to February 2022. Fertile healthy women were recruited from family planning clinic, oocyte donors and subfertile women from Gynaecology and ART clinic. AMH was done using ELISA, Beckmann Coulter Gen II assay and AFC was done using TVS with high frequency probe (9.0 MHZ, Voluson,S-6, GE Healthcare, USA) by trained personnel. R Statistical Programming Language was used for statistical modelling and visualization. Age-specific AFC centile chart and AMH centile chart were generated using GAMLSS (Generalized Additive Models for Location Scale and Shape) package available in R Statistical Computing Language. A Non-linear decline in ovarian reserves among fertile, while linear among infertile women was seen. Centiles defined for both groups with a faster decline in infertile women. Age cut off for decline in AMH and AFC in fertile women approximately 31 years using ROC analysis and Age cut off for decline in AMH and AFC in infertile women is approximately 34 years. There seems to be a good correlation between AFC and AMH. We need to counsel women to consider child bearing well before ovarian reserves decline (31-34 years).

Four-wave mixing model for centrosymmetric constellation shaping in twin-wave-based coherent OFDM system including intersymbol interference

The four-wave-mixing (FWM) noises are modeled when walk-off and intersymbol interference (ISI) are taken into account for any centrosymmetric constellation shaped signal in orthogonal frequency-division multiplexed (OFDM) with phase-conjugated twin waves (PCTW) scheme. Bit error rate (BER) and the equivalent Q-factor for any constellation shaped signal are also modeled when the FWM and amplified spontaneous emission (ASE) noises are taken into account as additive white Gaussian noise. By using the newly derived semi-analytic models, example calculations are carried out for 16-ary signal in PCTW OFDM system with four cases classified according to some proposed constellation shaping schemes adopted or not. A hybrid constellation shaping scheme consisted of Huffman-coded probabilistic shaping and radius-optimized geometric shaping is proposed. The performance gain in terms of the equivalent Q-factor is calculated to be about 0.563 dB for 16-ary signal in PCTW OFDM system with the proposed hybrid constellation shaping scheme over the square conventional 16QAM signal. The performance degradation for such system due to the effects of ISI on the FWM noise is also evaluated by using the semi-analytic calculation models.

Normative Reference Centiles for Sprint Performance in High-Level Youth Soccer Players: The Need to Consider Biological Maturity.

To compute reference centiles for 5- and 30-m sprint times relative to chronological and skeletal age in youth soccer players. Subsequently, to compare individual's sprint performance scores derived from the chronological and skeletal age reference centiles. Sprint times were collected for a sample of male U11 to U19 soccer players (n = 1745 data points). Skeletal age data were available for a subsample (n = 776 data points). Reference centiles were fitted using generalized additive models for location, scale, and shape. Individual z scores relative to chronological and skeletal age reference centiles were computed and compared for each maturity group (late, on-time, early, and very early) using standardized mean differences (SMD). Reference centiles for chronological age increased more rapidly between 10.5 and 15.5years, while reference centiles for skeletal age increased more rapidly between 13.0 and 16.5years. Differences in chronological and skeletal z scores for very early (SMD: -0.73 to -0.43) and late (SMD: 0.58 to 1.29) maturing players were small to large, while differences for early (SMD: -0.30 to -0.19) and on-time (SMD: 0.16 to 0.28) were trivial to small. Reference centiles provide a valuable tool to assist the evaluation of sprint performance in relation to chronological and skeletal age for talent identification purposes in youth soccer players.

Mediation role of cardiorespiratory fitness on association of physical activity and physical literacy among 8-12 years old children: the PAK-IPPL cross-sectional study.

The effect of cardiorespiratory fitness (CRF) on the relationship of physical activity (PA), and physical literacy (PL) in 8-12 Pakistani children are largely unknown. Therefore, this study aims to examine the mediating role of CRF in the relationship between PA and PL in this demographic. This cross-sectional study involved 1,360 children aged 8-12 (mean age = 10.00, SD = 1.41 years) from 85 higher secondary schools in South Punjab, Pakistan. Data were collected during the 2020-2021 academic year using the Canadian Assessment of Physical Literacy-2 (CAPL-2) protocol to assess physical activity (PA), Body Mass Index (BMI), and PL levels. CRF was measured using the PACER (Progressive Aerobic Cardiovascular Endurance Run) test. Descriptive statistics, independent samples t-tests, Chi-squared tests, and Generalized Additive Models for Location, Scale, and Shape (GAMLSS) were used for age and sex-specific CAPL-2 scoring. Associations among components were evaluated through Pearson's correlation, multivariate logistic regression, and mediation analyses. The study revealed that boys had significantly higher scores in CRF, PA, and PL across all age groups compared to girls (p < 0.001), with boys' scores being 20%, 10%, and 14% higher, respectively, than those of girls. Conversely, overweight children showed significantly reduced PA and PL levels (p < 0.001). An inverse correlation was found between BMI and CRF (r 2 linear = 0.022; quadratic = 0.028). CRF scores had significant negative correlations BMI (r = -0.143) and positive associations with MVPA, PA, DB, and PL (r ranging from 0.241 to 0.624). CRF was observed to partially mediate the association between MVPA and PL. The direct impact of PA on PL was significant and meaningful (β = 0.002, p < .001). Additionally, the indirect effect of PA on PL through CRF was also significant (β = 0.001, p < .001), indicating that CRF serves as an important mediator in this relationship. The combined total effect of PA on PL, which includes both direct and mediated pathways, was robust and highly significant (β = 0.003, p < .001). The study revealed a strong positive correlation between CRF, PA, and PL, but a negative one with BMI in South Punjab children aged 8-12. Notably, CRF and PA emerged as significant predictors of PL levels in this population. Consequently, interventions that are both systematic and targeted towards improving these factors should be implemented as strategies to enhance children's PL levels and promote physically active behaviors.

Growth charts of Brazilian youngs: 20-years data of 95,000 children and adolescents from "Projeto Esporte Brasil".

This article aims to present growth curves for height, weight, and BMI of 95,000 Brazilian youths aged 6 to 17 years, including the five regions of the country, the Amazon region, and indigenous populations, and compare them with the World Health Organization (WHO) growth references. The final sample consisted of 52,729 boys and 42,731 girls from the "Projeto Esporte Brasil" database. Body mass and height information were used to derive the curves. The generalized additive model for location, scale, and shape was employed. In this study, we present smoothed weight-for-age, height-for-age, and BMI-for-age curves for boys and girls. Differences were observed between the results of the Brazilian curves and the WHO growth references. The developed curves will be valuable for professionals in medicine, public health, nutrition, physical education, and other related fields, regarding the assessment of physical growth in Brazilian children and adolescents and monitoring the nutritional status of this population. Additionally, these curves will facilitate the identification of individuals or subgroups at risk of diseases and delayed growth, with a greater focus on specific country-related factors.

Identification and analysis of evolution characteristics of flash drought based on three-dimensional perspective: A case study in the Jialing River basin

Flash drought is an extreme hydrological event, with a short foreseeable period and high destructive force, and it is difficult to monitor. Flash drought aggravates the risk of extreme disasters and seriously threatens agricultural production and urban water security. To explore the temporal and spatial dimension evolution and identifiable characteristics of flash drought, the present study proposed a comprehensive flash drought intensity (FDI) index to evaluate the severity of flash drought in the Jialing River Basin (JRB) based on the standardized evaporative stress ratio (SESR) method. In addition, the Normalized Area-Time Accumulation (NATA) curve was used to describe the three-dimensional continuous spatiotemporal evolution process of flash drought in the basin. The results showed that flash droughts lasted longer and were more severe in the highly urbanized southern part of the basin. In the past 40 years (1980–2020), the frequency, duration, and severity of flash droughts in the JRB increased. According to the susceptibility to flash drought, the JRB can be divided into four drought centers. Drought Center No. 1 is situated in the mountainous region in the northwest of the basin, exhibiting a high frequency of occurrence but affecting a relatively small area. In contrast, Drought Centers No. 2, 3, and 4 are located within urban areas, showing lower occurrence frequency but affecting a wider geographical expanse. Drought events with different developmental characteristics were compared using the NATA curve. Overall, the FD1 flash drought type, occurring in the early stages of drought, accounted for a significant proportion. Meanwhile, the accumulated area affected by FD3 and FD4 flash drought events in the later stages exceeded that of the FD2 flash drought type. In the later period, FD3 and FD4 flash drought events exhibited stronger growth momentum, thereby increasing the complexity and challenges of drought monitoring. The present study provides a theoretical basis for understanding the process, shape and evolution model of drought development under environmental changes as well as enables an enhanced early warning for flash droughts to improve management of water resources.

Softmax-Driven Active Shape Model for Segmenting Crowded Objects in Digital Pathology Images

Softmax-Driven Active Shape Model for Segmenting Crowded Objects in Digital Pathology Images

The spatial orientation of crista ampullaris: implications for BPPV diagnosis and treatment.

This study aimed to provide a comprehensive understanding of the spatial orientation of the crista ampullaris within the inner ear and its implications for the diagnosis and management of benign paroxysmal positional vertigo (BPPV). Using high-resolution MRI scans of 55 normal inner ears, 3D models of the semicircular canals were segmented. These were complemented by detailed membrane labyrinth models from micro-CT scans of human temporal bones, accessed via the Comparative Ear Bank (www.earbank.org). A statistical shape model of inner ears and eyeballs was established, and a standardized 3D spatial coordinate system was created. The horizontal plane was defined using the top of the common crus and the bottom of the eyeballs. This calibrated reference system allowed for precise quantification of crista ampullaris orientations by calculating angles between the defined crista planes and coordinate planes. The plane of the ampulla and the corresponding semicircular canal plane are nearly perpendicular to each other. In the upright position, the posterior semicircular canal crista ampullaris formed an angle of 48.9° with the horizontal plane. The relative orientations of the crista ampullaris of the lateral and superior canals were also defined. Furthermore, we identified "zero-point planes" representing crista orientations perpendicular to gravity, which resulted in minimal ampullary stimulation. A 6.2° tilt to the left in the supine position resulted in the plane of the left lateral semicircular canal crista ampullaris being parallel to the direction of gravity. This study elucidates the precise spatial orientation of the crista ampullaris, thereby providing an anatomical basis for understanding BPPV pathophysiology and improving the accuracy of diagnostic and therapeutic maneuvers. The findings have the potential to significantly enhance the management of BPPV and other inner ear disorders.

Responses of Simulated Arctic Mixed-Phase Clouds to Parameterized Ice Particle Shape

Abstract In simulations of Arctic mixed-phase clouds, cloud persistence and the liquid water path (LWP) are sensitive to ice particle number concentrations. Here, we explore sensitivities of cloud microphysical properties to the dominant ice particle shape (dendrites, plates, columns, or spheres) using the SCALE-AMPS large-eddy simulation model. AMPS is a bin microphysics scheme that predicts particle shapes based on the inherent growth ratio (IGR) of spheroids, which determines vapor depositional growth rates along the a and c axes, and the rimed and aggregate mass fractions. We examine the impacts of various IGR values on simulations of clouds observed during the M-PACE and SHEBA experiments. Under M-PACE (SHEBA) conditions, LWP varies between 49 (1.1) and 230 (6.7) g m−2, and the ice water path (IWP) varies between 3 (0.03) and 40 (0.12) g m−2, depending on the ice shape. The lowest LWP and the highest IWP are obtained when columnar particles dominate because their low terminal velocities and large capacitance and collisional area result in large vapor deposition and riming rates, whereas the highest LWP and lowest IWP are obtained when spherical particles dominate because their vapor deposition and riming rates are low. Because ice particle shape significantly influences simulated Arctic mixed-phase clouds, reliable simulations require accurately estimated IGR values under various atmospheric conditions. Finally, comparisons between the simulation results and observations show that the size distribution larger than 2000 μm is better reproduced when the increase in rimed mass that causes ice particles to become spherical is suppressed. Significance Statement Atmospheric models have difficulties in reproducing Arctic mixed-phase clouds because of uncertainties in the parameterization of microphysical processes. This is the first study to use a large-eddy simulation model implemented with a habit-predicting bin microphysics scheme to demonstrate the important role of ice particle shape on the microphysical properties of both heavy-riming and no-riming mixed-phase clouds. We found the vapor deposition and riming rates to be greatly influenced by ice particle shape. By comparing the ice particle size distribution, mass–diameter relationship, and area ratio between simulation results and observations, we show that a hexagonal ice shape model and a riming model that simply converts ice crystals to graupel may not accurately reproduce actual heavy-riming clouds.

Burden Surface Shape Modeling and Charging Matrix Optimization for the Blast Furnace Charging Process

Burden Surface Shape Modeling and Charging Matrix Optimization for the Blast Furnace Charging Process