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Article ; Online: Prediction of Fracture Toughness of Pultruded Composites Based on Supervised Machine Learning.

Karamov, Radmir / Akhatov, Iskander / Sergeichev, Ivan V

2022 Volume 14, Issue 17

Abstract: Prediction of mechanical properties is an essential part of material design. State-of-the-art simulation-based prediction requires data on microstructure and inter-component interactions of material. However, due to high costs and time limitations, such ... ...

Abstract	Prediction of mechanical properties is an essential part of material design. State-of-the-art simulation-based prediction requires data on microstructure and inter-component interactions of material. However, due to high costs and time limitations, such parameters, which are especially required for the simulation of advanced properties, are not always available. This paper proposes a data-driven approach to predicting the labor-consuming fracture toughness based on a series of standard, easy-to-measure mechanical characteristics. Three supervised machine-learning (ML) models (artificial neural networks, a random forest algorithm, and gradient boosting) were designed and tested for the prediction of mechanical properties of pultruded composites. A considerable dataset of mechanical properties was acquired as results of standard tensile, compression, flexure, in-plane shear, and Charpy tests and utilized as the input to predict the fracture toughness. Furthermore, this study investigated the correlations between the obtained mechanical characteristics. Analysis of ML performance showed that fracture toughness had the highest correlations with longitudinal bending and transverse tension and a strong correlation with the longitudinal compression modulus and tensile strength. The gradient boosting decision tree-based algorithms demonstrated the best prediction performance for fracture toughness, with an MSE less than 10% of the average value, providing a prediction within the range of experimental error. The ML algorithms showed potential in terms of determining which macro-level parameters can be used to predict micro-level material characteristics and how. The results provide inspiration for future pultruded composite material design and can enhance the numerical simulations of material.
Language	English
Publishing date	2022-09-01
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym14173619
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: High Tunable BaTi

Tumarkin, Andrei / Sapego, Evgeny / Gagarin, Alexander / Karamov, Artem

Molecules (Basel, Switzerland)

2022 Volume 27, Issue 18

Abstract: In this study, the structural and microwave properties of ... ...

Abstract	In this study, the structural and microwave properties of BaTiZrO
MeSH term(s)	Aluminum Oxide ; Microwaves ; Temperature ; Titanium/chemistry ; X-Ray Diffraction
Chemical Substances	Titanium (D1JT611TNE) ; Aluminum Oxide (LMI26O6933)
Language	English
Publishing date	2022-09-18
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	1413402-0
ISSN	1420-3049 ; 1431-5165 ; 1420-3049
ISSN (online)	1420-3049
ISSN	1431-5165 ; 1420-3049
DOI	10.3390/molecules27186086
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Article ; Online: Super-Resolution Processing of Synchrotron CT Images for Automated Fibre Break Analysis of Unidirectional Composites.

Karamov, Radmir / Breite, Christian / Lomov, Stepan V / Sergeichev, Ivan / Swolfs, Yentl

Polymers

2023 Volume 15, Issue 9

Abstract: Fibre breaks govern the strength of unidirectional composite materials under tension. The progressive development of fibre breaks is studied using in situ X-ray computed tomography, especially with synchrotron radiation. However, even with synchrotron ... ...

Abstract	Fibre breaks govern the strength of unidirectional composite materials under tension. The progressive development of fibre breaks is studied using in situ X-ray computed tomography, especially with synchrotron radiation. However, even with synchrotron radiation, the resolution of the time-resolved in situ images is not sufficient for a fully automated analysis of continuous mechanical deformations. We therefore investigate the possibility of increasing the quality of low-resolution in situ scans by means of super-resolution (SR) using 3D deep learning techniques, thus facilitating the subsequent fibre break identification. We trained generative neural networks (GAN) on datasets of high-(0.3 μm) and low-resolution (1.6 μm) statically acquired images. These networks were then applied to a low-resolution (1.1 μm) noisy image of a continuously loaded specimen. The statistical parameters of the fibre breaks used for the comparison are the number of individual breaks and the number of 2-plets and 3-plets per specimen volume. The fully automated process achieves an average accuracy of 82% of manually identified fibre breaks, while the semi-automated one reaches 92%. The developed approach allows the use of faster, low-resolution in situ tomography without losing the quality of the identified physical parameters.
Language	English
Publishing date	2023-05-06
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym15092206
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Article ; Online: Prediction of Fracture Toughness of Pultruded Composites Based on Supervised Machine Learning

Radmir Karamov / Iskander Akhatov / Ivan V. Sergeichev

Polymers, Vol 14, Iss 3619, p

2022 Volume 3619

Abstract	Prediction of mechanical properties is an essential part of material design. State-of-the-art simulation-based prediction requires data on microstructure and inter-component interactions of material. However, due to high costs and time limitations, such parameters, which are especially required for the simulation of advanced properties, are not always available. This paper proposes a data-driven approach to predicting the labor-consuming fracture toughness based on a series of standard, easy-to-measure mechanical characteristics. Three supervised machine-learning (ML) models (artificial neural networks, a random forest algorithm, and gradient boosting) were designed and tested for the prediction of mechanical properties of pultruded composites. A considerable dataset of mechanical properties was acquired as results of standard tensile, compression, flexure, in-plane shear, and Charpy tests and utilized as the input to predict the fracture toughness. Furthermore, this study investigated the correlations between the obtained mechanical characteristics. Analysis of ML performance showed that fracture toughness had the highest correlations with longitudinal bending and transverse tension and a strong correlation with the longitudinal compression modulus and tensile strength. The gradient boosting decision tree-based algorithms demonstrated the best prediction performance for fracture toughness, with an MSE less than 10% of the average value, providing a prediction within the range of experimental error. The ML algorithms showed potential in terms of determining which macro-level parameters can be used to predict micro-level material characteristics and how. The results provide inspiration for future pultruded composite material design and can enhance the numerical simulations of material.
Keywords	composite materials ; pultrusion ; fracture toughness ; machine learning ; correlation ; Organic chemistry ; QD241-441
Subject code	620
Language	English
Publishing date	2022-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Big data technology in infectious diseases modeling, simulation, and prediction after the COVID-19 outbreak.

Shi, Honghao / Wang, Jingyuan / Cheng, Jiawei / Qi, Xiaopeng / Ji, Hanran / Struchiner, Claudio J / Villela, Daniel Am / Karamov, Eduard V / Turgiev, Ali S

Intelligent medicine

2023 Volume 3, Issue 2, Page(s) 85–96

Abstract: After the outbreak of COVID-19, the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods. Starting from the research purpose and data, researchers improved the structure and data of ... ...

Abstract	After the outbreak of COVID-19, the interaction of infectious disease systems and social systems has challenged traditional infectious disease modeling methods. Starting from the research purpose and data, researchers improved the structure and data of the compartment model or used agents and artificial intelligence based models to solve epidemiological problems. In terms of modeling methods, the researchers use compartment subdivision, dynamic parameters, agent-based model methods, and artificial intelligence related methods. In terms of factors studied, the researchers studied 6 categories: human mobility, nonpharmaceutical interventions (NPIs), ages, medical resources, human response, and vaccine. The researchers completed the study of factors through modeling methods to quantitatively analyze the impact of social systems and put forward their suggestions for the future transmission status of infectious diseases and prevention and control strategies. This review started with a research structure of research purpose, factor, data, model, and conclusion. Focusing on the post-COVID-19 infectious disease prediction simulation research, this study summarized various improvement methods and analyzes matching improvements for various specific research purposes.
Language	English
Publishing date	2023-01-20
Publishing country	China
Document type	Journal Article
ISSN	2667-1026
ISSN (online)	2667-1026
DOI	10.1016/j.imed.2023.01.002
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Article ; Online: Non-Conjugated Copoly(Arylene Ether Ketone) for the Current-Collecting System of a Solar Cell with Indium Tin Oxide Electrode.

Lachinov, Alexey N / Karamov, Danfis D / Galiev, Azat F / Salazkin, Sergey N / Shaposhnikova, Vera V / Kost, Tatiana N / Chebotareva, Alla B

Polymers

2023 Volume 15, Issue 4

Abstract: The mechanism of charge carrier transport in the indium tin oxide (ITO)/polymer/Cu structure is studied, where thin films of copoly(arylene ether ketone) with cardo fluorene moieties are used. This copoly(arylene ether ketone) is non-conjugated polymer ... ...

Abstract	The mechanism of charge carrier transport in the indium tin oxide (ITO)/polymer/Cu structure is studied, where thin films of copoly(arylene ether ketone) with cardo fluorene moieties are used. This copoly(arylene ether ketone) is non-conjugated polymer which has the properties of electronic switching from the insulating to the highly conductive state. The dependence on the polymer film thickness of such parameters as the potential barrier at the ITO/polymer interface, the concentration of charge carriers, and their mobility in the polymer is studied for the first time. The study of this system is of interest due to the proven potential of using the synthesized polymer in the contact system of a silicon solar cell with an ITO top layer. The parameters of charge carriers and ITO/polymer barrier are evaluated based on the analysis of current-voltage characteristics of ITO/polymer/Cu structure within the injection current models and the Schottky model. The thickness of the polymer layer varies from 50 nm to 2.1 µm. The concentration of intrinsic charge carriers increases when decreasing the polymer film thickness. The charge carrier mobility depends irregularly on the thickness, showing a maximum of 9.3 × 10
Language	English
Publishing date	2023-02-13
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym15040928
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Article ; Online: Non-Conjugated Poly(Diphenylene Phthalide)-New Electroactive Material.

Karamov, Danfis D / Galiev, Azat F / Lachinov, Alexey A / Davlyatgareev, Khalim I / Salazkin, Sergey N / Yakhin, Artur R / Lachinov, Alexey N

Polymers

2023 Volume 15, Issue 16

Abstract: In organic electronics, conjugated conductive polymers are most widely used. The scope of their application is currently very wide. Non-conjugated polymers are used much less in electronics and are usually used as insulation materials or materials for ... ...

Abstract	In organic electronics, conjugated conductive polymers are most widely used. The scope of their application is currently very wide. Non-conjugated polymers are used much less in electronics and are usually used as insulation materials or materials for capacitors. However, the potential of non-conjugated polymers is much wider, due to the fact that new electronic materials with unique electronic properties can be created on the basis of non-conjugated polymers, as well as other inorganic dielectrics. This article demonstrates the possibilities of creating electrically conductive materials with unique electronic parameters based on non-conjugated polymers. The results of the study of the sensory properties of humidity are given as examples of the practical application of the structure. The abnormal electronic properties are realized along the interface of two polymer dielectrics with functional polar groups. The submicron films of polydiphenylenephthalide were used as a dielectric. It is shown that a quasi-two-dimensional electronic structure with abnormally large values of conductivity and mobility of charge carriers occurs along the interface. These structures are often called quasi-two-dimensional electron gas (Q2DEG). This article describes the manufacturing processes of multielectrode devices. Polymer films are deposited via the spin-coating method with polymer solutions in cyclohexanone. The metal electrodes were manufactured through thermal deposition in a vacuum. Three types of metal electrodes made of aluminum, copper and chromium were used. The influence of the electron work function of contacting metals on the electronic parameters of the structure was studied. It was established that the work function decrease leads to an increase in the conductivity and mobility of charge carriers. The charge carrier parameters were estimated based on the analysis of the current-voltage characteristics within the space-charge-limited current technique. The Richardson-Schottky thermionic emission model was used to evaluate values a potential barrier at metal/organic interfaces. It was established that the change in ambient humidity strongly affects the electronic transport properties along the polymer/polymer interface. It is demonstrated that the increase in conductivity with an increase in humidity occurs due to an increase in the mobility of charge carriers and a decrease in the height of the potential barrier at the three-dimensional metal contact with two-dimensional polymer interface. The potential barrier between the electrode and the bulk of the polymer film is significantly higher than between the electrode and the quasi-two-dimensional polymer structure.
Language	English
Publishing date	2023-08-10
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym15163366
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Article: Installed capacity optimization of autonomous photovoltaic systems under energy service contracting

Karamov, Dmitriy N / Minarchenko, Ilya M / Kolosnitsyn, Anton V / Pavlov, Nikita V

Energy conversion and management. 2021 July 15, v. 240

2021

Abstract: Various mechanisms have been developed worldwide to support renewable energy sources. These mechanisms promote greater integration of renewable energy sources into power supply systems. Many support mechanisms can operate only in centralized power ... ...

Abstract	Various mechanisms have been developed worldwide to support renewable energy sources. These mechanisms promote greater integration of renewable energy sources into power supply systems. Many support mechanisms can operate only in centralized power systems with well-structured market relations. As far as autonomous power systems are concerned, high expectations are placed on energy service contracting which offers a number of advantages such as instant investment, absence of risks for local authorities, fuel savings and efficient technical solutions.This paper presents a methodology for installed capacity optimization of autonomous photovoltaic systems under energy service contracting. The proposed methodology is based on the chronological method for calculating power supply systems using multi-year meteorological data sets. The study uses classical mathematical models of components of power supply systems: solar panels, solar inverters and direct current combiner boxes with allowance for operational restrictions. The internal optimization algorithm is described for the installed capacity and standard size of solar inverters and direct current combiner boxes. A hierarchical two-stage model for interaction between energy service company and regional authorities is proposed. The installed capacity of the Tyoply Klyuch photovoltaic system (Far East, Russia) has been optimized. The optimization process took into consideration nine types of solar panels: monocrystalline, polycrystalline and heterojunction panels. The reported value of the installed capacity is 1600 kW under the nine-year long contract. The annual fuel economy constitutes 300 tons, and a profit for the energy service company is US$ 0.428 million at the expiration of the contract. The methodology described in the present paper is universal and can be applied throughout the world.
Keywords	Russia ; administrative management ; algorithms ; energy conversion ; markets ; meteorological data ; solar collectors
Language	English
Dates of publication	2021-0715
Publishing place	Elsevier Ltd
Document type	Article
ZDB-ID	2000891-0
ISSN	0196-8904
ISSN	0196-8904
DOI	10.1016/j.enconman.2021.114256
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Agent-Based Simulation of the COVID-19 Epidemic in Russia.

Rykovanov, G N / Lebedev, S N / Zatsepin, O V / Kaminskii, G D / Karamov, E V / Romanyukha, A A / Feigin, A M / Chetverushkin, B N

Herald of the Russian Academy of Sciences

2022 Volume 92, Issue 4, Page(s) 479–487

Abstract: The COVID-19 pandemic has created a public health emergency in Russia and across the world. The wavelike spread of the new coronavirus infection, caused by newly emerging variants of the coronavirus, has led to a high incidence rate in all subjects of ... ...

Abstract	The COVID-19 pandemic has created a public health emergency in Russia and across the world. The wavelike spread of the new coronavirus infection, caused by newly emerging variants of the coronavirus, has led to a high incidence rate in all subjects of the Russian Federation. It is becoming extremely topical to get the opportunity to manage the development of the epidemic and assess the impact of certain regulatory measures on this process. This will help government agencies make informed decisions to control the burden on healthcare organizations. It is often impossible to obtain such assessments without using modern mathematical models.
Language	English
Publishing date	2022-09-06
Publishing country	Russia (Federation)
Document type	Journal Article
ZDB-ID	2044580-5
ISSN	1555-6492 ; 1019-3316
ISSN (online)	1555-6492
ISSN	1019-3316
DOI	10.1134/S1019331622040219
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Article ; Online: Adequacy analysis of electric power systems with wind and solar power stations

Karamov Dmitriy / Perzhabinsky Sergey

E3S Web of Conferences, Vol 58, p

2018 Volume 02019

Abstract: We developed a new method of adequacy analysis of electric power systems with wind and solar power stations. There are storage batteries in the electric power system. Various types of storage batteries can be used in electric power systems. They are ... ...

Abstract	We developed a new method of adequacy analysis of electric power systems with wind and solar power stations. There are storage batteries in the electric power system. Various types of storage batteries can be used in electric power systems. They are electrochemical, hydroelectric, heat or air storages. The modelling of wind speed and solar radiation is based on software «Local analysis of environmental parameters and solar radiation». The original combination of modern models of meteorological data processing is used in the software. For adequacy analysis of electric power system, we use nonsingle estimation of electricity sacrifice in random hour. Simulation of random values is carried out by the Monte Carlo method.
Keywords	Environmental sciences ; GE1-350
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	EDP Sciences
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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