Regional simulation of long-term organic carbon stock changes in cropland soils using the DNDC model: 1. Large-scale model validation against a spatially explicit data set

2006 ◽  
Vol 22 (4) ◽  
pp. 342-351 ◽  
Author(s):  
S. Sleutel ◽  
S. De Neve ◽  
D. Beheydt ◽  
C. Li ◽  
G. Hofman
Keyword(s):  
Large Scale ◽  
Scale Model ◽  
Spatially Explicit ◽  
Dndc Model ◽  
Data Set ◽  
Large Scale Model ◽  
Regional Simulation ◽  
Spatially Explicit Data ◽  
Organic Carbon Stock

scholarly journals rascalc: a jackknife approach to estimating single- and multitracer galaxy covariance matrices

2019 ◽  
Vol 491 (3) ◽  
pp. 3290-3317 ◽  
Author(s):  
Oliver H E Philcox ◽  
Daniel J Eisenstein ◽  
Ross O’Connell ◽  
Alexander Wiegand
Keyword(s):  
Large Scale ◽  
Covariance Matrices ◽  
Scale Model ◽  
Data Sets ◽  
Data Set ◽  
Large Numbers ◽  
Large Scale Model ◽  
Point Correlation ◽  
Point Correlation Function ◽  
Single Input

ABSTRACT To make use of clustering statistics from large cosmological surveys, accurate and precise covariance matrices are needed. We present a new code to estimate large-scale galaxy two-point correlation function (2PCF) covariances in arbitrary survey geometries that, due to new sampling techniques, runs ∼104 times faster than previous codes, computing finely binned covariance matrices with negligible noise in less than 100 CPU-hours. As in previous works, non-Gaussianity is approximated via a small rescaling of shot noise in the theoretical model, calibrated by comparing jackknife survey covariances to an associated jackknife model. The flexible code, rascalc, has been publicly released, and automatically takes care of all necessary pre- and post-processing, requiring only a single input data set (without a prior 2PCF model). Deviations between large-scale model covariances from a mock survey and those from a large suite of mocks are found to be indistinguishable from noise. In addition, the choice of input mock is shown to be irrelevant for desired noise levels below ∼105 mocks. Coupled with its generalization to multitracer data sets, this shows the algorithm to be an excellent tool for analysis, reducing the need for large numbers of mock simulations to be computed.

Creep Characteristics of Organic Soft Clay Soil Using Large–Scale Model

2021 ◽  
Author(s):  
Raid Al-Omari ◽  
◽  
Mohammed Fattah ◽  
Mudhafar Hameedi ◽  
◽  
...  
Keyword(s):  
Large Scale ◽  
Large Fraction ◽  
Soft Clay ◽  
Laboratory Data ◽  
Soil Surface ◽  
Organic Content ◽  
Scale Model ◽  
Secondary Compression ◽  
Large Scale Model

The long-term settlements in organic clay can create a kind of an engineering challenge that appear in most facilities design and construction in areas with deep deposits of soft clay. Peat ground is widely distributed throughout the southern part of Iraq. Peat contains a large amount of organic matter and has a very high natural water content. Three soil samples were collected from depths of 1.5 m, 2.5 m, and 3.5 m, below the soil surface in Halfaya oilfield, which lies east of Missan governorate southern Iraq. A series of tests were conducted in a large-scale model using a plate footing and considering three different percent of organic content. The percent of secondary settlement found is dependent on the stress level applied. A large fraction of the total settlement may be due to secondary compression. The assumption of a constant coefficient of secondary compression, Cα, may not be valid for a long-term settlement of peats. Laboratory data indicate that Cα generally increases with time. Thus, settlement predictions using constant Cα may underestimate field settlement.

Dynamic Response of Pile-Board Subgrade Based on Large Scale Model Test

2011 ◽  
Vol 71-78 ◽  
pp. 383-387 ◽  
Author(s):  
Qian Su ◽  
Xing Li ◽  
Hao Bai
Keyword(s):  
Dynamic Response ◽  
Dynamic Load ◽  
Large Scale ◽  
Test Group ◽  
Structural Type ◽  
Scale Model ◽  
Load Frequency ◽  
Large Scale Model ◽  
Supporting Effect

A series of tests based on large scale model are designed to study dynamic response of pile-broad subgrade, aiming at structure’s response towards different load frequency and structure’s performance under long-term dynamic load. The test results indicate that dynamic stress of reinforcement and soil decrease slightly with load frequency, while accelerations trend to increase. Soil under loading plate has certain supporting effect because stress of reinforcement is smaller in test group with soil remains. Performance of pile-board subgrade under long-term dynamic load is steady and reliable since none of stress and displacement varies obviously when loading times increase to 106. Ultimate bearing capacity of pile-board subgrade is much bigger than actual demand, so the structural type of pile-broad plate remains to be optimized.

scholarly journals Novel Method to Analytically Obtain the Asymptotic Stable Equilibria States of Extended SIR-type Epidemiological Models

2021 ◽  
Author(s):  
Teddy Lazebnik ◽  
Svetlana Bunimovich-Mendrazitsky ◽  
Leonid Shaikhet
Keyword(s):  
Large Scale ◽  
Initial Conditions ◽  
Scale Model ◽  
Epidemiological Models ◽  
Stochastic Representation ◽  
Asymptotic Stable ◽  
Large Scale Model ◽  
Stable Equilibria ◽  
Novel Method

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the SIR-type epidemiological model that we developed for viral diseases with long-term immunity memory pandemic. This is a large-scale model containing 15 nonlinear ODE equations, and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions.

scholarly journals Incremental Parameter Estimation under Rank-Deficient Measurement Conditions

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 75 ◽  
Author(s):  
Kris Villez ◽  
Julien Billeter ◽  
Dominique Bonvin
Keyword(s):  
Parameter Estimation ◽  
Large Scale ◽  
Model Identification ◽  
Scale Model ◽  
Parameter Estimation Problem ◽  
Data Set ◽  
Large Scale Model ◽  
Estimation Problems ◽  
Important Barrier ◽  
System Partitioning

The computation and modeling of extents has been proposed to handle the complexity of large-scale model identification tasks. Unfortunately, the existing extent-based framework only applies when certain conditions apply. Most typically, it is required that a unique value for each extent can be computed. This severely limits the applicability of this approach. In this work, we propose a novel procedure for parameter estimation inspired by the existing extent-based framework. A key difference with prior work is that the proposed procedure combines structural observability labeling, matrix factorization, and graph-based system partitioning to split the original model parameter estimation problem into parameter estimation problems with the least number of parameters. The value of the proposed method is demonstrated with an extensive simulation study and a study based on a historical data set collected to characterize the isomerization of α -pinene. Most importantly, the obtained results indicate that an important barrier to the application of extent-based frameworks for process modeling and monitoring tasks has been lifted.

scholarly journals Novel Method to Analytically Obtain the Asymptotic Stable Equilibria States of Extended SIR-Type Epidemiological Models

Symmetry ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1120
Author(s):  
Teddy Lazebnik ◽  
Svetlana Bunimovich-Mendrazitsky ◽  
Leonid Shaikhet
Keyword(s):  
Large Scale ◽  
Initial Conditions ◽  
Scale Model ◽  
Epidemiological Models ◽  
Stochastic Representation ◽  
Asymptotic Stable ◽  
Large Scale Model ◽  
Stable Equilibria ◽  
Novel Method

We present a new analytical method to find the asymptotic stable equilibria states based on the Markov chain technique. We reveal this method on the Susceptible-Infectious-Recovered (SIR)-type epidemiological model that we developed for viral diseases with long-term immunity memory. This is a large-scale model containing 15 nonlinear ordinary differential equations (ODEs), and classical methods have failed to analytically obtain its equilibria. The proposed method is used to conduct a comprehensive analysis by a stochastic representation of the dynamics of the model, followed by finding all asymptotic stable equilibrium states of the model for any values of parameters and initial conditions thanks to the symmetry of the population size over time.

RANCANG BANGUN PERANGKAT EKSPERIMENTASI PROSES PIROLISIS BIOMASA GELOMBANG MIKRO

2013 ◽  
Vol 14 (2) ◽  
Author(s):  
Noor Fachrizal
Keyword(s):  
Large Scale ◽  
Continuous Model ◽  
Biomass Energy ◽  
Scale Model ◽  
Small Scale ◽  
Laboratory Apparatus ◽  
Liquid Form ◽  
Large Scale Model ◽  
Bio Oil ◽  
Pyrolysis Of Biomass

Biomass such as agriculture waste and urban waste are enormous potency as energy resources instead of enviromental problem. organic waste can be converted into energy in the form of liquid fuel, solid, and syngas by using of pyrolysis technique. Pyrolysis process can yield higher liquid form when the process can be drifted into fast and flash response. It can be solved by using microwave heating method. This research is started from developing an experimentation laboratory apparatus of microwave-assisted pyrolysis of biomass energy conversion system, and conducting preliminary experiments for gaining the proof that this method can be established for driving the process properly and safely. Modifying commercial oven into laboratory apparatus has been done, it works safely, and initial experiments have been carried out, process yields bio-oil and charcoal shortly, several parameters are achieved. Some further experiments are still needed for more detail parameters. Theresults may be used to design small-scale continuous model of productionsystem, which then can be developed into large-scale model that applicable for comercial use.

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