scholarly journals Numerical Study of the 10 January 1998 Lake-Effect Bands Observed during Lake-ICE

2005 ◽  
Vol 62 (9) ◽  
pp. 3232-3249 ◽  
Author(s):  
Gregory J. Tripoli
Keyword(s):  
Lake Michigan ◽  
Numerical Study ◽  
Real Data ◽  
Streamwise Vorticity ◽  
Lake Ice ◽  
Fine Grid ◽  
Near Surface ◽  
Wave Trapping ◽  
Initial Location ◽  
Grid Nesting

Abstract This paper presents the results of a series of idealized cloud resolving simulations of the evolution of moist roll convection observed as part of the Lake-Induced Convection Experiment (Lake-ICE) that took place during the 1997/98 winter over central Lake Michigan. Satellite and radar observations of the roll convection depict striking linear rolls stretching from 10 km off the western shore of the lake, across to the eastern shore, and then continuing across Michigan. The spacing of the primary rolls was observed to be 6 km, giving a ratio of spacing to depth of about 5:1, which is consistent with theory. In addition, a longer wavelength (13 km) of stationary banding was observed parallel to the shoreline. In an earlier study of this case, multiply nested simulations of the convective rolls based on real data variable initialization were successful in producing banded structures with similar spacing and location over the water to those observed using fine grid resolution of about 500 m. Unfortunately, the initial locations of simulated bands were organized primarily by numerical effects of grid interpolation. This suggested that the spacing of the bands was robust, but that their initial location was highly sensitive to subtle systematic forcings. In this paper, a set of idealized model experiments, designed to isolate the role that physically realistic local forcing plays in the organization of the rolls, was performed. Because externally generated upstream turbulence was suppressed in these tests so as not to bias the result, the generation of rolls was delayed until 20–30 km downwind of the observed location and the location simulated in the previous grid nesting experiments. It was shown that the subtle effects of the shoreline geometry were sufficient to spawn a near-surface streamwise vorticity that became the primary seed for roll development at the most efficient mode of roll convection. These results suggest that previous structures evolved in the upstream shear-driven land-based mixed layer were likely also important in determining where the nonlocal overturning was first triggered. It is not clear from these results whether the shear-driven structures that evolved over the land also played a significant role in organizing the structural geometry of the lake rolls. Results also suggested that the shore parallel bands were a robust feature of the atmospheric structure resulting from resonant gravity wave trapping in the frontal layer.

scholarly journals Robust estimation for multivariate wrapped models

METRON ◽  
2021 ◽  
Author(s):  
Giovanni Saraceno ◽  
Claudio Agostinelli ◽  
Luca Greco
Keyword(s):  
Robust Estimation ◽  
Numerical Study ◽  
Real Data ◽  
Likelihood Method ◽  
Weighted Likelihood ◽  
Finite Sample ◽  
Pearson Residuals ◽  
Data Points ◽  
Wrapped Distributions ◽  
Standard Techniques

AbstractA weighted likelihood technique for robust estimation of multivariate Wrapped distributions of data points scattered on a $$p-$$ p - dimensional torus is proposed. The occurrence of outliers in the sample at hand can badly compromise inference for standard techniques such as maximum likelihood method. Therefore, there is the need to handle such model inadequacies in the fitting process by a robust technique and an effective downweighting of observations not following the assumed model. Furthermore, the employ of a robust method could help in situations of hidden and unexpected substructures in the data. Here, it is suggested to build a set of data-dependent weights based on the Pearson residuals and solve the corresponding weighted likelihood estimating equations. In particular, robust estimation is carried out by using a Classification EM algorithm whose M-step is enhanced by the computation of weights based on current parameters’ values. The finite sample behavior of the proposed method has been investigated by a Monte Carlo numerical study and real data examples.

Regularization and datuming of seismic data by weighted, damped least squares

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. U67-U76 ◽  
Author(s):  
Robert J. Ferguson
Keyword(s):  
Least Squares ◽  
Seismic Data ◽  
Synthetic Data ◽  
Real Data ◽  
Structural Data ◽  
Irregular Sampling ◽  
Data Set ◽  
Near Surface ◽  
Damped Least Squares ◽  
Wavefield Extrapolation

The possibility of improving regularization/datuming of seismic data is investigated by treating wavefield extrapolation as an inversion problem. Weighted, damped least squares is then used to produce the regularized/datumed wavefield. Regularization/datuming is extremely costly because of computing the Hessian, so an efficient approximation is introduced. Approximation is achieved by computing a limited number of diagonals in the operators involved. Real and synthetic data examples demonstrate the utility of this approach. For synthetic data, regularization/datuming is demonstrated for large extrapolation distances using a highly irregular recording array. Without approximation, regularization/datuming returns a regularized wavefield with reduced operator artifacts when compared to a nonregularizing method such as generalized phase shift plus interpolation (PSPI). Approximate regularization/datuming returns a regularized wavefield for approximately two orders of magnitude less in cost; but it is dip limited, though in a controllable way, compared to the full method. The Foothills structural data set, a freely available data set from the Rocky Mountains of Canada, demonstrates application to real data. The data have highly irregular sampling along the shot coordinate, and they suffer from significant near-surface effects. Approximate regularization/datuming returns common receiver data that are superior in appearance compared to conventional datuming.

scholarly journals Ground ice in the Northern Foothills, northern Victoria Land, Antarctica

2004 ◽  
Vol 39 ◽  
pp. 495-500 ◽  
Author(s):  
Mauro Guglielmin ◽  
Hugh M. French
Keyword(s):  
Oxygen Isotope ◽  
Ross Sea ◽  
Progress Report ◽  
Ground Ice ◽  
Lake Ice ◽  
Near Surface ◽  
Victoria Land ◽  
Different Types ◽  
Glacier Ice ◽  
Surface Ice

AbstractThis progress report classifies the different types of ground-ice bodies that occur in the Northern Foothills, northern Victoria Land, Antarctica. Oxygen isotope variations are presented, but interpretation is kept to a minimum pending further investigations. Surface ice, as distinct from moving glacier ice, occurs in the form of widespread buried (‘dead’) glacier ice lying beneath ablation (sublimation) till, together with perennial lake ice, snow banks and icing-blister ice.’Dry’ permafrost is uncommon, and interstitial ice is usually present at the base of the active layer and in the near-surface permafrost. This probably reflects the supply of moisture from the Ross Sea and limited sublimation under today’s climate. Intrusive ice occurs as layers within perennial lake-ice covers and gives rise to small icing blisters. Small ice wedges found beneath the furrows of high-centered polygons appear to agree with the model of sublimation-till development proposed by Marchant and others (2002).

FULL-WAVEFORM INVERSION WITH SOURCE AND RECEIVER COUPLING EFFECTS CORRECTION

Geophysics ◽  
2021 ◽  
pp. 1-37
Author(s):  
Xinhai Hu ◽  
Wei Guoqi ◽  
Jianyong Song ◽  
Zhifang Yang ◽  
Minghui Lu ◽  
...  
Keyword(s):  
Waveform Inversion ◽  
Nonlinear Least Squares ◽  
Real Data ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Linear Inversion ◽  
Near Surface ◽  
Model Parameter ◽  
Full Waveform ◽  
Coupling Factors

Coupling factors of sources and receivers vary dramatically due to the strong heterogeneity of near surface, which are as important as the model parameters for the inversion success. We propose a full waveform inversion (FWI) scheme that corrects for variable coupling factors while updating the model parameter. A linear inversion is embedded into the scheme to estimate the source and receiver factors and compute the amplitude weights according to the acquisition geometry. After the weights are introduced in the objective function, the inversion falls into the category of separable nonlinear least-squares problems. Hence, we could use the variable projection technique widely used in source estimation problem to invert the model parameter without the knowledge of source and receiver factors. The efficacy of the inversion scheme is demonstrated with two synthetic examples and one real data test.

scholarly journals Weighted Mask R-CNN for Improving Adjacent Boundary Segmentation

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
SungMin Suh ◽  
Yongeun Park ◽  
KyoungMin Ko ◽  
SeongMin Yang ◽  
Jaehyeong Ahn ◽  
...  
Keyword(s):  
Cell Membrane ◽  
Edge Detection ◽  
Numerical Study ◽  
Simulated Data ◽  
Real Data ◽  
Environmental Research ◽  
Single Image ◽  
Heterogeneous Objects ◽  
In Virtue Of ◽  
Instance Segmentation

In the recent era of AI, instance segmentation has significantly advanced boundary and object detection especially in diverse fields (e.g., biological and environmental research). Despite its progress, edge detection amid adjacent objects (e.g., organism cells) still remains intractable. This is because homogeneous and heterogeneous objects are prone to being mingled in a single image. To cope with this challenge, we propose the weighted Mask R-CNN designed to effectively separate overlapped objects in virtue of extra weights to adjacent boundaries. For numerical study, a range of experiments are performed with applications to simulated data and real data (e.g., Microcystis, one of the most common algae genera and cell membrane images). It is noticeable that the weighted Mask R-CNN outperforms the standard Mask R-CNN, given that the analytic experiments show on average 92.5% of precision and 96.4% of recall in algae data and 94.5% of precision and 98.6% of recall in cell membrane data. Consequently, we found that a majority of sample boundaries in real and simulated data are precisely segmented in the midst of object mixtures.

scholarly journals Two-grid full-waveform Rayleigh-wave inversion via a genetic algorithm — Part 1: Method and synthetic examples

Geophysics ◽  
2019 ◽  
Vol 84 (5) ◽  
pp. R805-R814 ◽  
Author(s):  
Zhen Xing ◽  
Alfredo Mazzotti
Keyword(s):  
Genetic Algorithm ◽  
Rayleigh Wave ◽  
A Priori ◽  
Computing Time ◽  
A Priori Information ◽  
Fine Grid ◽  
Near Surface ◽  
Reference Models ◽  
Full Waveform ◽  
Priori Information

When reliable a priori information is not available, it is difficult to correctly predict near-surface S-wave velocity models from Rayleigh waves through existing techniques, especially in the case of complex geology. To tackle this issue, we have developed a new method: two-grid genetic-algorithm Rayleigh-wave full-waveform inversion (FWI). Adopting a two-grid parameterization of the model, the genetic algorithm inverts for unknown velocities and densities at the nodes of a coarse grid, whereas the forward modeling is performed on a fine grid to avoid numerical dispersion. A bilinear interpolation brings the coarse-grid results into the fine-grid models. The coarse inversion grid allows for a significant reduction in the computing time required by the genetic algorithm to converge. With a coarser grid, there are fewer unknowns and less required computing time, at the expense of the model resolution. To further increase efficiency, our inversion code can perform the optimization using an offset-marching strategy and/or a frequency-marching strategy that can make use of different kinds of objective functions and allows for parallel computing. We illustrate the effect of our inversion method using three synthetic examples with rather complex near-surface models. Although no a priori information was used in all three tests, the long-wavelength structures of the reference models were fairly predicted, and satisfactory matches between “observed” and predicted data were achieved. The fair predictions of the reference models suggest that the final models estimated by our genetic-algorithm FWI, which we call macromodels, would be suitable inputs to gradient-based Rayleigh-wave FWI for further refinement. We also explored other issues related to the practical use of the method in different work and explored applications of the method to field data.

Optimal Parallel Machine Allocation Problem in IC Packaging Using IC-PSO: An Empirical Study

2017 ◽  
Vol 34 (06) ◽  
pp. 1750034
Author(s):  
Robert Cuckler ◽  
Kuo-Hao Chang ◽  
Liam Y. Hsieh
Keyword(s):  
Empirical Study ◽  
Stochastic Simulation ◽  
Integrated Circuit ◽  
Flow Shop ◽  
Numerical Study ◽  
Real Data ◽  
Solution Quality ◽  
Ic Packaging ◽  
Metamodeling Technique ◽  
Machine Allocation

We model and apply a stochastic-simulation-based methodology to optimize the machine allocation of a flexible flow shop (FFS) dedicated to integrated circuit (IC) packaging. This contrasts with most previous research on non-deterministic FFS problems wherein stochastic simulation is mostly used to estimate throughput, cycle time, delay cost, or some other measure(s) in order to compare the performances of already-existing heuristic-based algorithms. The methodology applied in this research, called progressive simulation metamodeling for IC Packaging (IC-PSO), while rooted in the traditional metamodeling technique known as Response Surface Methodology (RSM), contrasts with RSM in that it is equipped with well-designed mechanisms to ensure an ever-increasing solution quality in an attempt to achieve the desirable optimality. The computational efficiency that IC-PSO affords IC packaging companies is demonstrated via a numerical study. Meanwhile, an empirical study based on real data was conducted to validate the viability of the proposed methodology in real settings.

scholarly journals Experimental and Numerical Study of Behaviour of Reinforced Masonry Walls with NSM CFRP Strips Subjected to Combined Loads

Buildings ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 103
Author(s):  
Houria Hernoune ◽  
Benchaa Benabed ◽  
Antonios Kanellopoulos ◽  
Alaa Hussein Al-Zuhairi ◽  
Abdelhamid Guettala
Keyword(s):  
Failure Modes ◽  
Numerical Study ◽  
Masonry Wall ◽  
Brick Masonry ◽  
Masonry Walls ◽  
Near Surface ◽  
Combined Loads ◽  
Reinforced Masonry ◽  
Brick And Mortar ◽  
Near Surface Mounted

Near surface mounted (NSM) carbon fibers reinforced polymer (CFRP) reinforcement is one of the techniques for reinforcing masonry structures and is considered to provide significant advantages. This paper is composed of two parts. The first part presents the experimental study of brick masonry walls reinforced with NSM CFRP strips under combined shear-compression loads. Masonry walls have been tested under vertical compression, with different bed joint orientations 90° and 45° relative to the loading direction. Different reinforcement orientations were used including vertical, horizontal, and a combination of both sides of the wall. The second part of this paper comprises a numerical analysis of unreinforced brick masonry (URM) walls using the detailed micro-modelling approach (DMM) by means of ABAQUS software. In this analysis, the non-linearity behavior of brick and mortar was simulated using the concrete damaged plasticity (CDP) constitutive laws. The results proved that the application of the NSM-CFRP strips on the masonry wall influences significantly strength, ductility, and post-peak behavior, as well as changing the failure modes. The adopted DMM model provides a good interface to predict the post peak behavior and failure mode of unreinforced brick masonry walls.

Numerical modeling of refraction arrivals in complex areas

Geophysics ◽  
1985 ◽  
Vol 50 (1) ◽  
pp. 90-98 ◽  
Author(s):  
N. R. Hill ◽  
P. C. Wuenschel
Keyword(s):  
Numerical Modeling ◽  
Plane Wave ◽  
Complex Structure ◽  
Real Data ◽  
Synthetic Seismograms ◽  
Weak Signal ◽  
Surface Complex ◽  
Low Velocity ◽  
Near Surface ◽  
Plane Wave Field

Use of refracted arrivals to delineate near‐surface complex structure can sometimes be difficult because of rapid lateral changes in the refraction event along the line of control. The interpreter must correlate over zones of interference and zones of weak signal. During correlation it is often difficult to stay on the correct cycle of the waveform. We present a method to model refracted arrivals numerically in an area where these problems occur. The computation combines plane‐wave field decomposition to calculate propagation in complex regions with a WKBJ method to calculate propagation in simple regions. To illustrate the method, we study a case where the near‐surface complex structure is caused by the presence of low‐velocity gaseous mud. The modeling produces synthetic seismograms showing the interference patterns and changes in intensity that are seen in real data. This modeling shows how correlations may be done over difficult areas, particularly where cycle skips can occur.

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