Binary collision lattice simulation study of model parameters in monocrystalline sputtering

1989 ◽  
Vol 1 (28) ◽  
pp. 4697-4722 ◽  
Author(s):  
J Likonen ◽  
M Hautala
JETP Letters ◽  
2019 ◽  
Vol 110 (1) ◽  
pp. 1-4 ◽  
Author(s):  
V. V. Braguta ◽  
A. Yu. Kotov ◽  
A. A. Nikolaev

2006 ◽  
Vol 71 (8-9) ◽  
pp. 957-967 ◽  
Author(s):  
Ljiljana Markovska ◽  
Vera Meshko ◽  
Mirko Marinkovski

The isotherms and kinetics of zinc adsorption from aqueous solution onto granular activated carbon (GAC) and natural zeolite were studied using an agitated batch adsorber. The maximum adsorption capacities of GAC and natural zeolite towards zinc(II) from Langmuir adsorption isotherms were determined using experimental adsorption equilibrium data. The homogeneous solid diffusion model (HSD-model) combined with external mass transfer resistance was applied to fit the experimental kinetic data. The kinetics simulation study was performed using a computer program based on the proposed mathematical model and developed using gPROMS. As the two-mass transfer resistance approach was applied, two model parameters were fitted during the simulation study. External mass transfer and solid phase diffusion coefficients were obtained to predict the kinetic curves for varying initial Zn(II) concentration at constant agitation speed and constant adsorbent mass. For any particular Zn(II) - adsorbent system, k f was constant, except for the lowest initial concentration, while D s was found to increase with increasing initial Zn(II) concentration.


2019 ◽  
Vol 7 (1) ◽  
pp. 13-27
Author(s):  
Safaa K. Kadhem ◽  
Sadeq A. Kadhim

"This paper aims at the modeling the crashes count in Al Muthanna governance using finite mixture model. We use one of the most common MCMC method which is called the Gibbs sampler to implement the Bayesian inference for estimating the model parameters. We perform a simulation study, based on synthetic data, to check the ability of the sampler to find the best estimates of the model. We use the two well-known criteria, which are the AIC and BIC, to determine the best model fitted to the data. Finally, we apply our sampler to model the crashes count in Al Muthanna governance.


2012 ◽  
Vol 116 (33) ◽  
pp. 9963-9970
Author(s):  
Santiago Romero-Vargas Castrillón ◽  
Silvina Matysiak ◽  
Frank H. Stillinger ◽  
Peter J. Rossky ◽  
Pablo G. Debenedetti

2015 ◽  
Vol 77 (28) ◽  
Author(s):  
Siti Marhainis Othman ◽  
Mohd Fua’ad Rahmat ◽  
Sahazati Md. Rozali ◽  
Sazilah Salleh

Electro-hydraulic actuator (EHA) system inherently suffers from uncertainties, nonlinearities and time- varying in its model parameters which cause the modeling and controller designs are more complicated. Proportional Integral Derivative (PID) control scheme has been proposed and the main problem with its application is to tune the parameters to its optimum values. This study will look into an optimization of PID parameters using particle swarm optimization (PSO). Simulation study has been done in Matlab and Simulink. 


Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1786 ◽  
Author(s):  
A. M. Abd El-Raheem ◽  
M. H. Abu-Moussa ◽  
Marwa M. Mohie El-Din ◽  
E. H. Hafez

In this article, a progressive-stress accelerated life test (ALT) that is based on progressive type-II censoring is studied. The cumulative exposure model is used when the lifetime of test units follows Pareto-IV distribution. Different estimates as the maximum likelihood estimates (MLEs) and Bayes estimates (BEs) for the model parameters are discussed. Bayesian estimates are derived while using the Tierney and Kadane (TK) approximation method and the importance sampling method. The asymptotic and bootstrap confidence intervals (CIs) of the parameters are constructed. A real data set is analyzed in order to clarify the methods proposed through this paper. Two types of the progressive-stress tests, the simple ramp-stress test and multiple ramp-stress test, are compared through the simulation study. Finally, some interesting conclusions are drawn.


JETP Letters ◽  
2015 ◽  
Vol 101 (11) ◽  
pp. 732-734 ◽  
Author(s):  
V. V. Braguta ◽  
A. Yu. Kotov ◽  
A. A. Nikolaev ◽  
S. N. Valgushev

2018 ◽  
Author(s):  
Florie Gosseau ◽  
Nicolas Blanchet ◽  
Didier Varès ◽  
Philippe Burger ◽  
Didier Campergue ◽  
...  

AbstractHeliaphen is an outdoor pot platform designed for high-throughput phenotyping. It allows automated management of drought scenarios and plant monitoring during the whole plant cycle. A robot moving between plants growing in 15L pots monitors plant water status and phenotypes plant or leaf morphology, from which we can compute more complex traits such as the response of leaf expansion (LE) or plant transpiration (TR) to water deficit. Here, we illustrate the platform capabilities for sunflower on two practical cases: a genetic and genomics study for the response to drought of yield-related traits and a simulation study, where we use measured parameters as inputs for a crop simulation model. For the genetic study, classical measurements of thousand-kernel weight (TKW) were done on a sunflower bi-parental population under water stress and control conditions managed automatically. The association study using the TKW drought-response highlighted five genetic markers. A complementary transcriptomic experiment identified closeby candidate genes differentially expressed in the parental backgrounds in drought conditions. For the simulation study, we used the SUNFLO crop simulation model to assess the impact of two traits measured on the platform (LE and TR) on crop yield in a large population of environments. We conducted simulations in 42 contrasted locations across Europe and 21 years of climate data. We defined the pattern of abiotic stresses occurring at this continental scale and identified ideotypes (i.e. genotypes with specific traits values) that are more adapted to specific environment types. This study exemplifies how phenotyping platforms can help with the identification of the genetic architecture of complex response traits and the estimation of eco-physiological model parameters in order to define ideotypes adapted to different environmental conditions.


Author(s):  
Fadhah Alanazi

Uncovering hidden mixture correlation among variables have been investigating in the literature using mixture R-vine copula models. These models are hierarchical in nature. They provides a huge flexibility for modelling multivariate data. As the dimensions increases, the number of the model parameters that need to be estimated is increased dramatically, which becomes along with huge computational times and efforts. This situation becomes even much more harder and complicated in the mixture Regular vine models. Incorporating truncation method with mixture Regular vine models will reduce the computation difficulty for the mixture based models. In this paper, tree-by-tree estimation mixture model is joined with the truncation method, in order to reduce the computational time and the number of the parameters that need to be estimated in the mixture vine copula models. A simulation study and a real data applications illustrated the performance of the method. In addition, the real data applications show the affect of the mixture components on the truncation level.


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