A5061369039- Material Properties and Applications
- Titanium Alloys Microstructure and Properties
- Metal and Thin Film Mechanics
- Hydrogen embrittlement and corrosion behaviors in metals
- Climate variability and models
- Material Properties and Failure Mechanisms
- Engineering Technology and Methodologies
- Surface Treatment and Coatings
- Engineering Diagnostics and Reliability
- Aluminum Alloy Microstructure Properties
- Intermetallics and Advanced Alloy Properties
- Microstructure and Mechanical Properties of Steels
- Metallurgical Processes and Thermodynamics
- Climate Change Policy and Economics
- Pigment Synthesis and Properties
- Shape Memory Alloy Transformations
- Iron and Steelmaking Processes
- Aluminum Alloys Composites Properties
- Medical and Biological Sciences
- Nuclear Materials and Properties
- Extraction and Separation Processes
- Recycling and utilization of industrial and municipal waste in materials production
- Oceanographic and Atmospheric Processes
- Minerals Flotation and Separation Techniques
- Glass properties and applications
Karaganda State Industrial University
2024
Irkutsk National Research Technical University
2024
Ivanovo State University of Chemistry and Technology
2014-2023
Chuvash State University
2023
Yaroslavl State Technical University
2019-2021
Moscow Aviation Institute
1988-2020
Moscow State University of Fine Chemical Technologies
2015-2017
Moscow Power Engineering Institute
2016
Moscow State Aviation Technological University
1980-2015
University of Technology
2006-2015
Abstract. Climate models contain closure parameters to which the model climate is sensitive. These appear in physical parameterization schemes where some unresolved variables are expressed by predefined rather than being explicitly modeled. Currently, best expert knowledge used define optimal parameter values, based on observations, process studies, large eddy simulations, etc. Here, estimation, adaptive Markov chain Monte Carlo (MCMC) method, applied for estimation of joint posterior...
Abstract. Many dynamical models, such as numerical weather prediction and climate contain so called closure parameters. These parameters usually appear in physical parameterizations of sub-grid scale processes, they act "tuning handles" the models. Currently, values these are specified mostly manually, but increasing complexity models calls for more algorithmic ways to perform tuning. Traditionally, systems estimated by directly comparing model simulations observed data using, instance, a...
Abstract The article identifies the key sources of iron and boron impurities entering silicon metal under industrial smelting conditions in Submerged arc furnace (SAF). Impurity rocks composition quartz, main raw material for production metal, were studied using X-ray fluorescence method, their visual classification was carried out. It has been established that energy secondary characteristic x-ray radiation (CXR) contained feedstock is 3.1 6.3 keV, respectively. A relationship found between...
Abstract. The extended Kalman filter (EKF) is a popular state estimation method for nonlinear dynamical models. model error covariance matrix often seen as tuning parameter in EKF, which simply postulated by the user. In this paper, we study likelihood technique estimating parameters of matrix. approach based on computing using filtering output. We show that (a) importance calibration depends quality observations, and (b) yields well-tuned EKF terms accuracy estimates predictions. For our...
Changes in a dynamical process are often detected by monitoring selected indicators directly obtained from the observations, such as mean values or variances. Standard change detection algorithms Shewhart control charts cumulative sum (CUSUM) algorithm based on first- and second-order statistics. Much better results can be if is properly modeled, for example nonlinear state-space model, then accuracy of model monitored over time. The success latter approach depends largely quality model. In...
Denoising source separation (DSS), a recently developed framework, was applied to extracting components exhibiting slow, interannual temporal behavior from climate data. Three datasets with daily measurements were used: surface temperature, sea level pressure and precipitation around the globe. For all datasets, first extracted component captured well-known El Nino-Southern Oscillation phenomenon second close derivative of one. Several other slow dynamics together appear capture essential...