Level of Detail and Multi-Resolution Modeling Techniques for Virtual Design and Prototyping

1999 ◽  
Author(s):  
Zhigeng Pan ◽  
Kun Zhou ◽  
Chiyi Cheng ◽  
Mingmin Zhang
Keyword(s):  
Virtual Reality ◽  
Large Scale ◽  
Level Of Detail ◽  
Data Sets ◽  
Virtual Design ◽  
Variable Resolution ◽  
Modeling Techniques ◽  
Resolution Model ◽  
Cad Models ◽  
Representation Scheme

Abstract Reconciling scene realism with interactivity has emerged as one of the most important areas in making virtual reality feasible for large-scale CAD data sets consisting of several millions of primitives. Level of detail (LoD) and multi-resolution modeling techniques in virtual reality can be used to speedup the process of virtual design and virtual prototyping. In this paper we present an automatic LoD generation and rendering algorithm which is suitable for CAD models and propose a new multi-resolution representation scheme called MRM (multi-resolution model), which can support efficient extraction of fixed resolution and variable resolution for multiple objects in the same scene. MRM scheme supports unified selective simplifications and selective refinements over the mesh. Furthermore, LoD and multi-resolution models may be used to support real-time geometric transmission in collaborative virtual design and prototyping.

LEVEL OF DETAIL AND MULTI-RESOLUTION MODELING FOR VIRTUAL PROTOTYPING

2001 ◽  
Vol 01 (02) ◽  
pp. 329-343 ◽  
Author(s):  
ZHIGENG PAN ◽  
MINGMIN ZHANG ◽  
KUN ZHOU ◽  
CHIYI CHENG ◽  
JIAOYING SHI
Keyword(s):  
Virtual Reality ◽  
Large Scale ◽  
Virtual Prototyping ◽  
Level Of Detail ◽  
Data Sets ◽  
Virtual Design ◽  
Resolution Model ◽  
Cad Models ◽  
Speed Up ◽  
Representation Scheme

Reconciling scene realism with interactivity has emerged as one of the most important areas in making virtual reality feasible for large-scale CAD data sets consisting of several millions of primitives. Level of detail (LoD) and multi-resolution modeling techniques in virtual reality can be used to speed up the process of virtual design and virtual prototyping. In this paper, we present an automatic LoD generation and rendering algorithm, which is suitable for CAD models and propose a new multi-resolution representation scheme called MRM (multi-resolution model), which can support efficient extraction of fixed resolution and variable resolution for multiple objects in the same scene. MRM scheme supports unified selective simplifications and selective refinements over the mesh. Furthermore, LoD and multi-resolution models may be used to support real-time geometric transmission in collaborative virtual design and prototyping.

scholarly journals Multi-Resolution Modeling for Virtual Design

2000 ◽  
Vol 4 (4) ◽  
pp. 110-120 ◽  
Author(s):  
Chiyi Cheng ◽  
Mingmin Zhang ◽  
Zhigeng Pan
Keyword(s):  
Virtual Reality ◽  
Virtual Prototyping ◽  
Virtual Design ◽  
Multiple Objects ◽  
Variable Resolution ◽  
Modeling Techniques ◽  
Efficient Extraction ◽  
Key Features ◽  
Modeling Data ◽  
Representation Scheme

The benefits of multi-resolution modeling techniques in virtual reality are vast, but one essential component of this model is how it can be used to speedup the process of virtual design and virtual prototyping. In this paper we propose a new multi-resolution representation scheme called MRM, which can support efficient extraction of both fixed and variable resolution modeling data for handling multiple objects in the same scene. One important feature of the MRM scheme is that it supports unified selective simplifications and selective refinements over the mesh representation of the object. In addition, multi-resolution models may be used to support real-time geometric transmission of data in collaborative virtual design and prototyping applications. These key features in MRM, may be applied to a variety of VR applications.

Limits of the WTQ method for calculating momentum flux

2020 ◽  
Author(s):  
Peter Preusse ◽  
Markus Geldenhuys ◽  
Manfred Ern
Keyword(s):  
Gravity Wave ◽  
Momentum Flux ◽  
Large Scale ◽  
Vertical Gradient ◽  
Data Sets ◽  
Flux Vector ◽  
Intrinsic Frequency ◽  
Single Wave ◽  
Resolution Model ◽  
High Resolution Model

<p>The acceleration of the large scale circulation by gravity wave is commonly described via the vertical gradient of the vertical flux of horizontal pseudomomentum, or in short of the momentum flux. The momentum flux vector is given by</p><p> (F<sub>px</sub>,F<sub>py</sub>) = (1-f<sup>2</sup>/ω<sup>2</sup>) ( <u'w'>,<v'w'>)</p><p>where < > describes the spatial or temporal mean of at least one wavelength or period of the gravity wave. If one is going actually to calculate momentum flux from an observation or high-resolution model, several difficulties arise. First, one has to know the intrinsic frequency ω of the wave, second one tacitly assumes that only a single wave is causing the wind perturbations u', v' and w', and third one needs to find an appropriate averaging interval. One possibility to solve this is to perform spectral analysis. An alternative was introduced by Geller et al. (2013) which, based on the polarization relations, infers ω directly from the perturbation wind temperature quadratics and is hence referred to as WTQ. In a brief study we will investigate the implication of the single wave assumption for the momentum flux calculated from data sets calculating multiple waves.</p>

scholarly journals Toward Convective-Scale Prediction within the Next Generation Global Prediction System

2019 ◽  
Vol 100 (7) ◽  
pp. 1225-1243 ◽  
Author(s):  
Linjiong Zhou ◽  
Shian-Jiann Lin ◽  
Jan-Huey Chen ◽  
Lucas M. Harris ◽  
Xi Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Cloud Microphysics ◽  
Squall Line ◽  
Uniform Mesh ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Prediction System ◽  
Next Generation ◽  
Variable Resolution ◽  
Convective Scale ◽  
Resolution Model

AbstractThe Geophysical Fluid Dynamics Laboratory (GFDL) has developed a new variable-resolution global model with the ability to represent convective-scale features that serves as a prototype of the Next Generation Global Prediction System (NGGPS). The goal of this prediction system is to maintain the skill in large-scale features while simultaneously improving the prediction skill of convectively driven mesoscale phenomena. This paper demonstrates the new capability of this model in convective-scale prediction relative to the current operational Global Forecast System (GFS). This model uses the stretched-grid functionality of the Finite-Volume Cubed-Sphere Dynamical Core (FV3) to refine the global 13-km uniform-resolution model down to 4-km convection-permitting resolution over the contiguous United States (CONUS), and implements the GFDL single-moment 6-category cloud microphysics to improve the representation of moist processes. Statistics gathered from two years of simulations by the GFS and select configurations of the FV3-based model are carefully examined. The variable-resolution FV3-based model is shown to possess global forecast skill comparable with that of the operational GFS while quantitatively improving skill and better representing the diurnal cycle within the high-resolution area compared to the uniform mesh simulations. Forecasts of the occurrence of extreme precipitation rates over the southern Great Plains are also shown to improve with the variable-resolution model. Case studies are provided of a squall line and a hurricane to demonstrate the effectiveness of the variable-resolution model to simulate convective-scale phenomena.

Influences of Large-Scale Flow Variations on the Track Evolution of Typhoons Morakot (2009) and Megi (2010): Simulations with a Global Variable-Resolution Model

2017 ◽  
Vol 145 (5) ◽  
pp. 1691-1716 ◽  
Author(s):  
Ching-Yuang Huang ◽  
You Zhang ◽  
William C. Skamarock ◽  
Li-Huan Hsu
Keyword(s):  
Large Scale ◽  
Extreme Rainfall ◽  
Mountain Range ◽  
Variable Resolution ◽  
The North ◽  
Positive Vorticity ◽  
Resolution Model ◽  
Global Variable ◽  
Southern Taiwan ◽  
Large Scale Flow

Abstract Influences of large-scale flow variations on the track evolution of two typhoons, moderate Morakot (2009) and superintense Megi (2010), are investigated using the global variable-resolution model MPAS with a higher-resolution region of 15 km for the simulated typhoons. For Morakot, the associated track and extreme rainfall over southern Taiwan captured by MPAS compared well with the regional WRF simulations. To isolate the influences of various large-scale flows, three modes are filtered out from global reanalysis: the synoptic-scale mode, quasi-biweekly oscillation (QBW) mode, and the Madden–Julian oscillation (MJO) mode. In the absence of QBW or MJO, the simulated Morakot moves westward across Taiwan without the observed north turn after landfall. When the intensity of the MJO mode is increased by 50% in the experiment (MJO+50%), a much earlier northward turn is induced. The simulated Morakot under the observed MJO lies in between MJO+50% and MJO−50% results. The MJO variations also show similar impacts on the track evolution of Typhoon Megi. The wavenumber-1 decompositions of vorticity budget terms are shown to highlight important contributions to the vorticity tendency and typhoon translation with and without the MJO. The northward turn of both typhoons in the presence of the MJO is mainly in response to positive horizontal vorticity advection to the north of the typhoon center. However, vorticity tilting is relatively more important for Morakot due to its slantwise structure. Furthermore, positive vorticity stretching and vertical advection are significant in the vicinity of southern Taiwan due to the effects of the Central Mountain Range and tend to retard the departing Morakot.

scholarly journals Galaxy spin direction distribution in HST and SDSS show similar large-scale asymmetry

2020 ◽  
Vol 37 ◽  
Author(s):  
Lior Shamir
Keyword(s):  
Large Scale ◽  
Spiral Galaxies ◽  
Hubble Space Telescope ◽  
Gravitational Interaction ◽  
Large Data ◽  
Sloan Digital Sky Survey ◽  
Data Sets ◽  
Dipole Axis ◽  
Data Set ◽  
The Asymmetry

Abstract Several recent observations using large data sets of galaxies showed non-random distribution of the spin directions of spiral galaxies, even when the galaxies are too far from each other to have gravitational interaction. Here, a data set of $\sim8.7\cdot10^3$ spiral galaxies imaged by Hubble Space Telescope (HST) is used to test and profile a possible asymmetry between galaxy spin directions. The asymmetry between galaxies with opposite spin directions is compared to the asymmetry of galaxies from the Sloan Digital Sky Survey. The two data sets contain different galaxies at different redshift ranges, and each data set was annotated using a different annotation method. The results show that both data sets show a similar asymmetry in the COSMOS field, which is covered by both telescopes. Fitting the asymmetry of the galaxies to cosine dependence shows a dipole axis with probabilities of $\sim2.8\sigma$ and $\sim7.38\sigma$ in HST and SDSS, respectively. The most likely dipole axis identified in the HST galaxies is at $(\alpha=78^{\rm o},\delta=47^{\rm o})$ and is well within the $1\sigma$ error range compared to the location of the most likely dipole axis in the SDSS galaxies with $z>0.15$ , identified at $(\alpha=71^{\rm o},\delta=61^{\rm o})$ .

scholarly journals Accelerating In-Transit Co-Processing for Scientific Simulations Using Region-Based Data-Driven Analysis

Algorithms ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 154
Author(s):  
Marcus Walldén ◽  
Masao Okita ◽  
Fumihiko Ino ◽  
Dimitris Drikakis ◽  
Ioannis Kokkinakis
Keyword(s):  
Large Scale ◽  
Data Driven ◽  
Data Sets ◽  
Output Constraints ◽  
Data Driven Approach ◽  
Scientific Simulations ◽  
Multiple Metrics ◽  
In Transit ◽  
Multiple Compression ◽  
Large Scale Simulations

Increasing processing capabilities and input/output constraints of supercomputers have increased the use of co-processing approaches, i.e., visualizing and analyzing data sets of simulations on the fly. We present a method that evaluates the importance of different regions of simulation data and a data-driven approach that uses the proposed method to accelerate in-transit co-processing of large-scale simulations. We use the importance metrics to simultaneously employ multiple compression methods on different data regions to accelerate the in-transit co-processing. Our approach strives to adaptively compress data on the fly and uses load balancing to counteract memory imbalances. We demonstrate the method’s efficiency through a fluid mechanics application, a Richtmyer–Meshkov instability simulation, showing how to accelerate the in-transit co-processing of simulations. The results show that the proposed method expeditiously can identify regions of interest, even when using multiple metrics. Our approach achieved a speedup of 1.29× in a lossless scenario. The data decompression time was sped up by 2× compared to using a single compression method uniformly.

scholarly journals Compartment and hub definitions tune metabolic networks for metabolomic interpretations

GigaScience ◽  
2020 ◽  
Vol 9 (1) ◽  
Author(s):  
T Cameron Waller ◽  
Jordan A Berg ◽  
Alexander Lex ◽  
Brian E Chapman ◽  
Jared Rutter
Keyword(s):  
Large Scale ◽  
Metabolic Networks ◽  
Shortest Paths ◽  
Large Data ◽  
Differential Regulation ◽  
Large Data Sets ◽  
Data Sets ◽  
Human Metabolism ◽  
Experimental Conditions ◽  
Systemic Model

Abstract Background Metabolic networks represent all chemical reactions that occur between molecular metabolites in an organism’s cells. They offer biological context in which to integrate, analyze, and interpret omic measurements, but their large scale and extensive connectivity present unique challenges. While it is practical to simplify these networks by placing constraints on compartments and hubs, it is unclear how these simplifications alter the structure of metabolic networks and the interpretation of metabolomic experiments. Results We curated and adapted the latest systemic model of human metabolism and developed customizable tools to define metabolic networks with and without compartmentalization in subcellular organelles and with or without inclusion of prolific metabolite hubs. Compartmentalization made networks larger, less dense, and more modular, whereas hubs made networks larger, more dense, and less modular. When present, these hubs also dominated shortest paths in the network, yet their exclusion exposed the subtler prominence of other metabolites that are typically more relevant to metabolomic experiments. We applied the non-compartmental network without metabolite hubs in a retrospective, exploratory analysis of metabolomic measurements from 5 studies on human tissues. Network clusters identified individual reactions that might experience differential regulation between experimental conditions, several of which were not apparent in the original publications. Conclusions Exclusion of specific metabolite hubs exposes modularity in both compartmental and non-compartmental metabolic networks, improving detection of relevant clusters in omic measurements. Better computational detection of metabolic network clusters in large data sets has potential to identify differential regulation of individual genes, transcripts, and proteins.

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