A novel parameter inversion method for an improved DEM simulation of a river damming process by a large-scale landslide

2021 ◽  
pp. 106282
Author(s):  
Wen-Jie Xu ◽  
Qiang Xu ◽  
Guang-Yu Liu ◽  
Hui-Ya Xu
Keyword(s):  
Large Scale ◽  
Inversion Method ◽  
Dem Simulation ◽  
River Damming ◽  
Parameter Inversion

scholarly journals A New Hybrid Inversion Method for 2D Nuclear Magnetic Resonance Combining TSVD and Tikhonov Regularization

2021 ◽  
Vol 7 (2) ◽  
pp. 18
Author(s):  
Germana Landi ◽  
Fabiana Zama ◽  
Villiam Bortolotti
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Tikhonov Regularization ◽  
Large Scale ◽  
Regularization Parameter ◽  
High Sensitivity ◽  
Inversion Method ◽  
Nmr Relaxometry ◽  
Value Decomposition ◽  
Nuclear Magnetic

This paper is concerned with the reconstruction of relaxation time distributions in Nuclear Magnetic Resonance (NMR) relaxometry. This is a large-scale and ill-posed inverse problem with many potential applications in biology, medicine, chemistry, and other disciplines. However, the large amount of data and the consequently long inversion times, together with the high sensitivity of the solution to the value of the regularization parameter, still represent a major issue in the applicability of the NMR relaxometry. We present a method for two-dimensional data inversion (2DNMR) which combines Truncated Singular Value Decomposition and Tikhonov regularization in order to accelerate the inversion time and to reduce the sensitivity to the value of the regularization parameter. The Discrete Picard condition is used to jointly select the SVD truncation and Tikhonov regularization parameters. We evaluate the performance of the proposed method on both simulated and real NMR measurements.

On large scale CFD–DEM simulation for gas–liquid–solid three-phase flows

Particuology ◽  
2020 ◽  
Author(s):  
Kimiaki Washino ◽  
Ei L. Chan ◽  
Tetsushi Kaji ◽  
Yoshiaki Matsuno ◽  
Toshitsugu Tanaka
Keyword(s):  
Large Scale ◽  
Dem Simulation ◽  
Three Phase

scholarly journals Watermasses as a unifying framework for understanding the Southern Ocean carbon cycle

2010 ◽  
Vol 7 (3) ◽  
pp. 3393-3451 ◽  
Author(s):  
D. Iudicone ◽  
I. Stendardo ◽  
O. Aumont ◽  
K. B. Rodgers ◽  
G. Madec ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Large Scale ◽  
Thermohaline Circulation ◽  
Model Simulation ◽  
Polar Front ◽  
Global Ocean ◽  
Inversion Method ◽  
Co2 Fluxes ◽  
Meridional Transport ◽  
Regional Patterns

Abstract. A watermass-based framework is presented for a quantitative understanding of the processes controlling the cycling of carbon in the Southern Ocean. The approach is developed using a model simulation of the global carbon transports within the ocean and with the atmosphere. It is shown how the watermass framework sheds light on the interplay between biology, air-sea gas exchange, and internal ocean transport including diapycnal processes, and the way in which this interplay controls the large-scale ocean-atmosphere carbon exchange. The simulated pre-industrial regional patterns of DIC distribution and the global distribution of the pre-industrial air-sea CO2 fluxes compare well with other model results and with results from an ocean inversion method. The main differences are found in the Southern Ocean where the model presents a stronger CO2 outgassing south of the polar front, a result of the upwelling of DIC-rich deep waters into the surface layer. North of the subantarctic front the typical temperature-driven solubility effect produces a net ingassing of CO2. The biological controls on surface CO2 fluxes through primary production is generally smaller than the temperature effect on solubility. Novel to this study is also a Lagrangian trajectory analysis of the meridional transport of DIC. The analysis allows to evaluate the contribution of separate branches of the global thermohaline circulation (identified by watermasses) to the vertical distribution of DIC throughout the Southern Ocean and towards the global ocean. The most important new result is that the overturning associated with Subantarctic Mode Waters sustains a northward net transport of DIC (15.7×107 mol/s across 30° S). This new finding, which has also relevant implications on the prediction of anthropogenic carbon redistribution, results from the specific mechanism of SAMW formation and its source waters whose consequences on tracer transports are analyzed for the first time in this study.

scholarly journals Quantitative evaluation of the uncertainty sources for the modeling of atmospheric CO<sub>2</sub> concentration within and in the vicinity of Paris city

2020 ◽  
Author(s):  
Jinghui Lian ◽  
François-Marie Bréon ◽  
Grégoire Broquet ◽  
Bo Zheng ◽  
Michel Ramonet ◽  
...  
Keyword(s):  
Boundary Conditions ◽  
Co2 Emissions ◽  
Large Scale ◽  
Transport Model ◽  
Co2 Concentration ◽  
Inversion Method ◽  
Different Boundary Conditions ◽  
Paris Area ◽  
The City ◽  
Atmospheric Inversion

Abstract. The top-down atmospheric inversion method that couples atmospheric CO2 observations with an atmospheric transport model has been used extensively to quantify CO2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO2 that are of different origins than the targeted CO2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of one-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations and CO2 boundary conditions. The simulated CO2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime observation-model misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Our results suggest three selection criteria for the CO2 data to be assimilated for the inversion of CO2 emissions from Paris (i) discard data that appear as statistical outliers in the model-data misfits which are interpreted as model's deficiencies under complex meteorological conditions; (ii) use only afternoon urban measurements in winter and suburban ones in summer; (iii) test the influence of different boundary conditions in inversions. If possible, using additional observations to constrain the boundary inflow, or using CO2 gradients of upwind-downwind stations, rather than absolute CO2 concentration, as atmospheric inversion inputs.

Diagnosing the Scale and Space Dependent Horizontal Eddy Diffusivity at the Global Surface Ocean

2020 ◽  
Author(s):  
Aleksi Nummelin ◽  
Julius J. M. Busecke ◽  
Thomas W. N. Haine ◽  
Ryan P. Abernathey
Keyword(s):  
Large Scale ◽  
Inversion Method ◽  
Length Scale ◽  
Tracer Transport ◽  
Boundary Currents ◽  
Horizontal Mixing ◽  
Scale Range ◽  
The Tropics ◽  
Global Surface ◽  
Scale Shear

AbstractOceanic tracers are transported by oceanic motions of all scales, but only the large scale motions are resolved by the present-day Earth System Models. In these models, the unresolved lateral sub-gridscale tracer transport is generally parameterized through diffusive closures with a scale-independent diffusion coeffcient. However, evidence from observations and theory suggests that diffusivity varies spatially and is length-scale dependent. Here we provide new scale-dependent quantification of the global surface diffusivities. To this end we use a recently developed statistical inversion method, MicroInverse, to diagnose horizontal surface diffusivities from observed sea surface temperature and idealized model simulation. We compare the results to theoretical estimates of mixing by the large scale shear and by the sub-gridscale velocity fluctuations. The diagnosed diffusivity magnitude peaks in the tropics and western boundary currents with minima in the sub-tropical gyres (~3000 m2s−1 and ~100 m2s−1) at ~40 km scale, respectively. Focusing on the 40-200 km length scale range, we find that the diffusivity magnitude scales with the length scale to a power (n) that is between 1.22-1.54 (90% confidence) in the tropics and also peaks at values above 1 in the boundary currents. In the midlatitudes we find that 0:58 < n < 0:87 (90% confidence). Comparison to the theory suggests that in regions with n > 1 the horizontal mixing is dominated by large scale shear, whereas in regions where n < 1 the horizontal mixing is due to processes that are small compared to the 40-200 km length scale range considered in this study.

260 A Large-scale DEM Simulation using Realistic Shapes of Granular Particles on GPU

2015 ◽  
Vol 2015.28 (0) ◽  
pp. _260-1_-_260-2_
Author(s):  
Seiya WATANABE ◽  
Takayuki AOKI ◽  
Satori TSUZUKI
Keyword(s):  
Large Scale ◽  
Dem Simulation ◽  
Granular Particles

Study on the Particle Behavior in a Screw Conveyer System by the Discrete Element Method

2011 ◽  
Author(s):  
Yusuke Shigeto ◽  
Mikio Sakai ◽  
Shin Mizutani ◽  
Seiichi Koshizuka ◽  
Shuji Matsusaka
Keyword(s):  
Discrete Element Method ◽  
Large Scale ◽  
Discrete Element ◽  
Dem Simulation ◽  
Memory Space ◽  
Industrial Systems ◽  
Simulation Techniques ◽  
Conveyer System ◽  
Grain Model ◽  
Element Method

Large amount of particles are used in the industrial systems. Numerical analyses of these systems are expected to reduce designing cost. However the numerical analysis of powder is not used practically, because it requires high calculation cost which grows up with the number of particles. Besides, there are memory consumption problem which is required for calculation space. In this paper, the parallel simulation techniques of the Discrete Element Method (DEM) on multi-core processors are described. In the present study, it is shown that the algorithm enables all the processes of the DEM to be executed parallel. Moreover, a new algorithm which makes the memory space usage effectively and accelerates the calculation speed is proposed for multi-thread parallel computing of the DEM. In the present study, the memory space usage is shown to be reduced drastically by introducing this algorithm. In addition, the coarse grain model which emulates original particles with less calculation particles is applied in order to reduce calculation cost. For the practical usage of the DEM in industries, the simulation is performed in a large-scale powder system which possesses a complicated drive unit. In the current study, it is shown that the large scale DEM simulation of practical systems is enabled to be executed by our proposing algorithms.

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