scholarly journals Meteorological database using in developing of empirical (physical and statistical) hail storm cloud models

2019 ◽  
Vol 698 ◽  
pp. 044028
Author(s):  
V S Inuhin ◽  
I N Berezinsky
Keyword(s):  
Cloud Models ◽  
Storm Cloud

scholarly journals OICP: An Online Fast Registration Algorithm Based on Rigid Translation Applied to Wire Arc Additive Manufacturing of Mold Repair

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1563
Author(s):  
Ruibing Wu ◽  
Ziping Yu ◽  
Donghong Ding ◽  
Qinghua Lu ◽  
Zengxi Pan ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Point Cloud ◽  
Point Clouds ◽  
Iterative Closest Point ◽  
Multiple Point ◽  
Icp Algorithm ◽  
Registration Algorithm ◽  
Cloud Models ◽  
Comparison Results ◽  
Wire Arc Additive Manufacturing

As promising technology with low requirements and high depositing efficiency, Wire Arc Additive Manufacturing (WAAM) can significantly reduce the repair cost and improve the formation quality of molds. To further improve the accuracy of WAAM in repairing molds, the point cloud model that expresses the spatial distribution and surface characteristics of the mold is proposed. Since the mold has a large size, it is necessary to be scanned multiple times, resulting in multiple point cloud models. The point cloud registration, such as the Iterative Closest Point (ICP) algorithm, then plays the role of merging multiple point cloud models to reconstruct a complete data model. However, using the ICP algorithm to merge large point clouds with a low-overlap area is inefficient, time-consuming, and unsatisfactory. Therefore, this paper provides the improved Offset Iterative Closest Point (OICP) algorithm, which is an online fast registration algorithm suitable for intelligent WAAM mold repair technology. The practicality and reliability of the algorithm are illustrated by the comparison results with the standard ICP algorithm and the three-coordinate measuring instrument in the Experimental Setup Section. The results are that the OICP algorithm is feasible for registrations with low overlap rates. For an overlap rate lower than 60% in our experiments, the traditional ICP algorithm failed, while the Root Mean Square (RMS) error reached 0.1 mm, and the rotation error was within 0.5 degrees, indicating the improvement of the proposed OICP algorithm.

Overlapping Allografts Provide Superior and More Reliable Surface Topography Matching Than Oblong Allografts: A Computer-Simulated Model Study

2021 ◽  
pp. 036354652110030
Author(s):  
Hailey P. Huddleston ◽  
Atsushi Urita ◽  
William M. Cregar ◽  
Theodore M. Wolfson ◽  
Brian J. Cole ◽  
...  
Keyword(s):  
Articular Cartilage ◽  
Surface Topography ◽  
Osteochondral Allograft ◽  
Cartilage Defects ◽  
Radius Of Curvature ◽  
Cartilage Surface ◽  
3 Dimensional ◽  
Cloud Models ◽  
And Cartilage ◽  
Osteochondral Allografts

Background: Osteochondral allograft transplantation is 1 treatment option for focal articular cartilage defects of the knee. Large irregular defects, which can be treated using an oblong allograft or multiple overlapping allografts, increase the procedure’s technical complexity and may provide suboptimal cartilage and subchondral surface matching between donor grafts and recipient sites. Purpose: To quantify and compare cartilage and subchondral surface topography mismatch and cartilage step-off for oblong and overlapping allografts using a 3-dimensional simulation model. Study Design: Controlled laboratory study. Methods: Human cadaveric medial femoral hemicondyles (n = 12) underwent computed tomography and were segmented into cartilage and bone components using 3-dimensional reconstruction and modeling software. Segments were then exported into point-cloud models. Modeled defect sizes of 17 × 30 mm were created on each recipient hemicondyle. There were 2 types of donor allografts from each condyle utilized: overlapping and oblong. Grafts were virtually harvested and implanted to optimally align with the defect to provide minimal cartilage surface topography mismatch. Least mean squares distances were used to measure cartilage and subchondral surface topography mismatch and cartilage step-off. Results: Cartilage and subchondral topography mismatch for the overlapping allograft group was 0.27 ± 0.02 mm and 0.80 ± 0.19 mm, respectively. In comparison, the oblong allograft group had significantly increased cartilage (0.62 ± 0.43 mm; P < .001) and subchondral (1.49 ± 1.10 mm; P < .001) mismatch. Cartilage step-off was also found to be significantly increased in the oblong group compared with the overlapping group ( P < .001). In addition, overlapping allografts more reliably provided a significantly higher percentage of clinically acceptable (0.5- and 1-mm thresholds) cartilage surface topography matching (overlapping: 100% for both 0.5 and 1 mm; oblong: 90% for 1 mm and 56% for 0.5 mm; P < .001) and cartilage step-off (overlapping: 100% for both 0.5 and 1 mm; oblong: 86% for 1 mm and 12% for 0.5 mm; P < .001). Conclusion: This computer simulation study demonstrated improved topography matching and decreased cartilage step-off with overlapping osteochondral allografts compared with oblong osteochondral allografts when using grafts from donors that were not matched to the recipient condyle by size or radius of curvature. These findings suggest that overlapping allografts may be superior in treating large, irregular osteochondral defects involving the femoral condyles with regard to technique. Clinical Relevance: This study suggests that overlapping allografts may provide superior articular cartilage surface topography matching compared with oblong allografts and do so in a more reliable fashion. Surgeons may consider overlapping allografts over oblong allografts because of the increased ease of topography matching during placement.

scholarly journals What Polarimetric Weather Radars Offer to Cloud Modelers: Forward Radar Operators and Microphysical/Thermodynamic Retrievals

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 362 ◽  
Author(s):  
Alexander V. Ryzhkov ◽  
Jeffrey Snyder ◽  
Jacob T. Carlin ◽  
Alexander Khain ◽  
Mark Pinsky
Keyword(s):  
Cloud Model ◽  
Weather Prediction ◽  
Primary Source ◽  
Polarimetric Radar ◽  
Microphysical Process ◽  
Weather Radars ◽  
Cloud Models ◽  
Cloud Modeling ◽  
Bin Microphysics ◽  
The Impact

The utilization of polarimetric weather radars for optimizing cloud models is a next frontier of research. It is widely understood that inadequacies in microphysical parameterization schemes in numerical weather prediction (NWP) models is a primary cause of forecast uncertainties. Due to its ability to distinguish between hydrometeors with different microphysical habits and to identify “polarimetric fingerprints” of various microphysical processes, polarimetric radar emerges as a primary source of needed information. There are two approaches to leverage this information for NWP models: (1) radar microphysical and thermodynamic retrievals and (2) forward radar operators for converting the model outputs into the fields of polarimetric radar variables. In this paper, we will provide an overview of both. Polarimetric measurements can be combined with cloud models of varying complexity, including ones with bulk and spectral bin microphysics, as well as simplified Lagrangian models focused on a particular microphysical process. Combining polarimetric measurements with cloud modeling can reveal the impact of important microphysical agents such as aerosols or supercooled cloud water invisible to the radar on cloud and precipitation formation. Some pertinent results obtained from models with spectral bin microphysics, including the Hebrew University cloud model (HUCM) and 1D models of melting hail and snow coupled with the NSSL forward radar operator, are illustrated in the paper.

Comparison of Ice-Phase Microphysical Parameterization Schemes Using Numerical Simulations of Tropical Convection

1991 ◽  
Vol 30 (7) ◽  
pp. 985-1004 ◽  
Author(s):  
Michale McCumber ◽  
Wei-Kuo Tao ◽  
Joanne Simpson ◽  
Richard Penc ◽  
Su-Tzai Soong
Keyword(s):  
Cloud Model ◽  
Type Systems ◽  
Two Dimensions ◽  
Tropical Convection ◽  
Three Dimensions ◽  
Microphysical Properties ◽  
Cloud Models ◽  
Optimal Mix ◽  
Cloud Ice ◽  
Microphysical Parameterization

Abstract A numerical cloud model is used to evaluate the performance of several ice parameterizations. Results from simulations using these schemes are contrasted with each other, with an ice-free control simulation, and with observations to determine to what extent ice physics affect the realism of these results. Two different types of tropical convection are simulated. Tropical squall-type systems are simulated in two dimensions so that a large domain can be used to incorporate a complete anvil. Nonsquall-type convective lines are simulated in three dimensions owing to their smaller horizontal scale. The inclusion of ice processes enhances the agreement of the simulated convection with some features of observed convection, including the proportion of surface rainfall in the anvil region, and the intensity and structure of the radar brightband near the melting level in the anvil. In the context of our experimental design, the use of three ice classes produces better results than two ice classes or ice-free conditions, and for the tropical cumuli, the optimal mix of the bulk ice hydrometeors is cloud ice-snow-graupel. We infer from our modeling results that application of bulk ice microphysics in cloud models might be case specific, which is a significant limitation. This can have serious ramifications for microwave interpretation of cloud microphysical properties. Generalization of ice processes may require a larger number of ice categories than we have evaluated and/or the prediction of hydrometeor concentrations or particle-size spectra.

BlastFunction: A Full-stack Framework Bringing FPGA Hardware Acceleration to Cloud-native Applications

2022 ◽  
Vol 15 (2) ◽  
pp. 1-27
Author(s):  
Andrea Damiani ◽  
Giorgia Fiscaletti ◽  
Marco Bacis ◽  
Rolando Brondolin ◽  
Marco D. Santambrogio
Keyword(s):  
Heterogeneous Computing ◽  
Performance Metrics ◽  
State Of The Art ◽  
Hardware Acceleration ◽  
Standard Approach ◽  
Cloud Models ◽  
Experimental Campaign ◽  
Computing Platforms ◽  
Cloud Infrastructures

“Cloud-native” is the umbrella adjective describing the standard approach for developing applications that exploit cloud infrastructures’ scalability and elasticity at their best. As the application complexity and user-bases grow, designing for performance becomes a first-class engineering concern. As an answer to these needs, heterogeneous computing platforms gained widespread attention as powerful tools to continue meeting SLAs for compute-intensive cloud-native workloads. We propose BlastFunction, an FPGA-as-a-Service full-stack framework to ease FPGAs’ adoption for cloud-native workloads, integrating with the vast spectrum of fundamental cloud models. At the IaaS level, BlastFunction time-shares FPGA-based accelerators to provide multi-tenant access to accelerated resources without any code rewriting. At the PaaS level, BlastFunction accelerates functionalities leveraging the serverless model and scales functions proactively, depending on the workload’s performance. Further lowering the FPGAs’ adoption barrier, an accelerators’ registry hosts accelerated functions ready to be used within cloud-native applications, bringing the simplicity of a SaaS-like approach to the developers. After an extensive experimental campaign against state-of-the-art cloud scenarios, we show how BlastFunction leads to higher performance metrics (utilization and throughput) against native execution, with minimal latency and overhead differences. Moreover, the scaling scheme we propose outperforms the main serverless autoscaling algorithms in workload performance and scaling operation amount.

scholarly journals A Finite-Volume Solution with a Bidirectional Upwind Difference Scheme for the Three-Dimensional Radiative Transfer Equation

2007 ◽  
Vol 64 (11) ◽  
pp. 4098-4112 ◽  
Author(s):  
Haruma Ishida ◽  
Shoji Asano
Keyword(s):  
Radiative Transfer ◽  
Difference Scheme ◽  
Finite Volume ◽  
Spherical Harmonic ◽  
Transfer Equation ◽  
Three Dimensional ◽  
Harmonic Series ◽  
Simultaneous Linear Equation ◽  
Upwind Difference Scheme ◽  
Cloud Models

Abstract A new calculation scheme is proposed for the explicitly discretized solution of the three-dimensional (3D) radiation transfer equation (RTE) for inhomogeneous atmospheres. To separate the independent variables involved in the 3D RTE approach, the spherical harmonic series expansion was used to discretize the terms, depending on the direction of the radiance, and the finite-volume method was applied to discretize the terms, depending on the spatial coordinates. A bidirectional upwind difference scheme, which is a specialized scheme for the discretization of the partial differential terms in the spherical harmonic-transformed RTE, was developed to make the equation determinate. The 3D RTE can be formulated as a simultaneous linear equation, which is expressed in the form of a vector–matrix equation with a sparse matrix. The successive overrelaxation method was applied to solve this equation. Radiative transfer calculations of the solar radiation in two-dimensional cloud models have shown that this method can properly simulate the radiation field in inhomogeneous clouds. A comparison of the results obtained using this method with those using the Monte Carlo method shows reasonable agreement for the upward flux, the total downward flux, and the intensities of radiance.

scholarly journals Inhomogeneous Mixing in Lagrangian Cloud Models: Effects on the Production of Precipitation Embryos

2018 ◽  
Vol 76 (1) ◽  
pp. 113-133 ◽  
Author(s):  
Fabian Hoffmann ◽  
Takanobu Yamaguchi ◽  
Graham Feingold
Keyword(s):  
Turbulent Mixing ◽  
Cloud Model ◽  
Small Scale ◽  
New Approach ◽  
Air Masses ◽  
Lagrangian Particles ◽  
Cloud Models ◽  
Large Eddy ◽  
Salutary Effect ◽  
Linear Eddy Model

Abstract Although small-scale turbulent mixing at cloud edge has substantial effects on the microphysics of clouds, most models do not represent these processes explicitly, or parameterize them rather crudely. This study presents a first use of the linear eddy model (LEM) to represent unresolved turbulent mixing at the subgrid scale (SGS) of large-eddy simulations (LESs) with a coupled Lagrangian cloud model (LCM). The method utilizes Lagrangian particles to provide the trajectory of air masses within LES grid boxes, while the LEM is used to redistribute these air masses among the Lagrangian particles based on the local features of turbulence, allowing for the appropriate representation of inhomogeneous to homogeneous SGS mixing. The new approach has the salutary effect of mitigating spurious supersaturations. At low turbulence intensities, as found in the early stages of an idealized bubble cloud simulation, cloud-edge SGS mixing tends to be inhomogeneous and the new approach is shown to be essential for the production of raindrop embryos. At higher turbulence intensities, as found in a field of shallow cumulus, SGS mixing tends to be more homogeneous and the new approach does not significantly alter the results, indicating that a grid spacing of 20 m may be sufficient to resolve all relevant scales of inhomogeneous mixing. In both cases, droplet in-cloud residence times are important for the production of precipitation embryos in the absence of small-scale inhomogeneous mixing, either naturally due to strong turbulence or artificially as a result of coarse resolution or by not using the LEM as an SGS model.

scholarly journals Questions fly over ash-cloud models

Nature ◽  
2010 ◽  
Vol 464 (7293) ◽  
pp. 1253-1253 ◽  
Author(s):  
Katharine Sanderson
Keyword(s):  
Cloud Models ◽  
Ash Cloud
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