Lobachevskii Journal of Mathematics最新文献

From Texts to Knowledge Graph in the Semantic Library LibMeta 语义图书馆 LibMeta 从文本到知识图谱

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602625

O. M. Ataeva, V. A. Serebryakov, N. P. Tuchkova

{"title":"From Texts to Knowledge Graph in the Semantic Library LibMeta","authors":"O. M. Ataeva, V. A. Serebryakov, N. P. Tuchkova","doi":"10.1134/s1995080224602625","DOIUrl":"https://doi.org/10.1134/s1995080224602625","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The problem of constructing a knowledge graph for previously unprocessed scientific texts is studied. The task is to analyze the use of various machine processing methods for extracting text semantics using the example of an interdisciplinary subject area. The goal of the research is to create a semantic model of the subject area of an interdisciplinary scientific journal and use a knowledge graph to navigate through data. The semantic model is based on the ontology of the LibMeta library. Texts and metadata receive connections due to the processing procedure and become part of the ontology of the semantic library. The interdisciplinary subject area is integrated into the library content as a related area of the ‘‘mathematics’’ ontology of the LibMeta library. A comparison of texts is carried out according to different characteristics, thematic proximity, commonality of research methods and approaches, problem setting and their symbolic representation. The results of preliminary text processing and the results in the form of a knowledge graph integrated into the library content are presented. The formulation of the problem of constructing an ontology and a knowledge graph for an interdisciplinary subject area adjacent to mathematics is considered by the authors as part of the general problem of managing mathematical knowledge.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Propagation of Acoustic Waves in a Moving Monodispersed Gas Suspension 声波在移动的单分散气体悬浮液中的传播

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602376

E. A. Teregulova

引用次数: 0

Mathematical Model of Asphaltene Deposition During Oil Production 石油生产过程中沥青质沉积的数学模型

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602303

A. I. Nikiforov, G. A. Nikiforov

引用次数: 0

A Mathematical Model of Rod Lateral Oscillations Considering an External Tangential Load 考虑外部切向载荷的杆侧摆动数学模型

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602431

I. V. Kudinov, A. V. Pashin, Yu. A. Kryukov

引用次数: 0

Probabilistic Analysis of the Coefficients of Stochastic Differential Equations in Their Modeling of the Air–Sea Interaction in the North Atlantic 北大西洋海气相互作用模型中随机微分方程系数的概率分析

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602406

K. P. Belyaev, N. P. Tuchkova, K. A. Romashina

{"title":"Probabilistic Analysis of the Coefficients of Stochastic Differential Equations in Their Modeling of the Air–Sea Interaction in the North Atlantic","authors":"K. P. Belyaev, N. P. Tuchkova, K. A. Romashina","doi":"10.1134/s1995080224602406","DOIUrl":"https://doi.org/10.1134/s1995080224602406","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The observational data for 1979–2018 in the North Atlantic region\u0000have been used for the analysis of the heat fluxes. The dynamics\u0000of air-sea interaction between ocean and atmosphere has been\u0000modeled by the stochastic differential equation (SDE) which use\u0000the heat fluxes observations taken from those databased. The\u0000coefficients of the SDE represented the diffusion stochastic\u0000process have been statistically defined from the original dataset.\u0000Earlier the existence and uniqueness of the solution in strong\u0000sense of SDE generated by the modeled diffusion process has been\u0000proved. In the current work the drift and diffusion coefficients\u0000have been smoothed and approximated by the trigonometric functions\u0000with sought amplitude and phase characteristics within chosen\u0000year. Their spatial and temporal intra-annual variability of those\u0000characteristics has been studied and analyzed. Also, the\u0000corresponding Fokker–Planck–Kolmogorov (FPK) equation for the\u0000SDE with smoothed coefficients has been constructed and\u0000numerically solved. Numerical calculations realized on the\u0000Lomonosov-2 supercomputer of the Lomonosov Moscow State\u0000University.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142216976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Metric Effects in Event Space and Einstein’s Gravitation Theory 事件空间的度量效应与爱因斯坦引力理论

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s199508022460239x

P. A. Belov, S. A. Lurie

引用次数: 0

Numerical Simulation of Inverse Retrospective Problems for a Two-Dimensional Heat Equation 二维热方程逆回溯问题的数值模拟

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602583

S. A. Kolesnik, E. M. Stifeev

{"title":"Numerical Simulation of Inverse Retrospective Problems for a Two-Dimensional Heat Equation","authors":"S. A. Kolesnik, E. M. Stifeev","doi":"10.1134/s1995080224602583","DOIUrl":"https://doi.org/10.1134/s1995080224602583","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>The paper proposes a new, unique method for numerically solving inverse problems for nonlinear conditions using the example of the problem of restoring the initial condition for a two-dimensional heat equation with boundary conditions of the third kind. In this problem, the initial condition is an unknown function of two variables, and is determined from experimental temperature values. The proposed method is based on using the parametric identification method, the implicit gradient descent method and Tikhonov’s regularization method. An algorithm and a software package for numerical solution have been developed. The use of the implicit gradient descent method allowed for faster convergence (number of iterations) compared to zero-order methods. Numerous results of numerical experiments have been obtained and discussed. An analysis of the behavior of solution functions with and without the use of Tikhonov’s regularizing functional along with the impact of the regularizing parameter has been carried out. The results of computational experiments using the proposed numerical method showed that the error in the results obtained does not exceed the error in the experimental data due to the correct choice of the regularizing parameter.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonlinear Resonant Gas Oscillations in Resonators with Variable Cross-section 可变截面谐振器中的非线性共振气体振荡

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602170

D. A. Gubaidullin, B. A. Snigerev

{"title":"Nonlinear Resonant Gas Oscillations in Resonators with Variable Cross-section","authors":"D. A. Gubaidullin, B. A. Snigerev","doi":"10.1134/s1995080224602170","DOIUrl":"https://doi.org/10.1134/s1995080224602170","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In a number of studies, it has been shown that the geometry of an acoustic resonator strongly affects its resonant frequencies, as well as the nonlinear shape of the standing pressure waves generated inside the cavity. In this paper, we consider three resonators with different wall shapes (cone, exponential and bulb-shaped resonators) in which gas vibrations are formed due to an external periodic force. The acoustic field in the resonators is generated by the vibration of the left wall of the enclosure. The oscillation frequency of this wall is chosen so that the lowest acoustic mode can propagate along the resonator. The fully compressible form of the Navier–Stokes equations is used, and the explicit time-stepping algorithm is employed for modeling the motion of acoustic waves. The structure of acoustic flows of the second order, resulting from the interaction between the wave field and viscous effects on the walls, leads to the formation of flow patterns. These patterns can be revealed by averaging solutions over a specific period of time. To evaluate the performance of resonators, the pressure amplitude gain factor is used. This is defined as the ratio of pressure amplitude at the small end of the resonator to the pressure amplitude at its large end. It has been found that the best performance is observed in a flask-shaped resonator.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Estimation of Oil Reservoir Transmissivity and Storativity Fields Using a Radial Basis Function Network Based on Inverse Problem Solving 利用基于逆问题求解的径向基函数网络估算油藏渗透率和储量场

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s199508022460225x

V. P. Kosyakov, D. Yu. Legostaev

{"title":"Estimation of Oil Reservoir Transmissivity and Storativity Fields Using a Radial Basis Function Network Based on Inverse Problem Solving","authors":"V. P. Kosyakov, D. Yu. Legostaev","doi":"10.1134/s199508022460225x","DOIUrl":"https://doi.org/10.1134/s199508022460225x","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>In the oil industry, there is a noticeable trend towards using proxy models to simulate various levels of complexity in order to make operational predictions. In particular, machine learning techniques are being actively developed in the context of the digitalization and automation of production processes. This paper proposes a method for combining a physically relevant fluid flow model with machine learning techniques to address the challenges of history-matching and prediction. The approach is demonstrated using synthetic oil reservoir models. The synthetic model has significant zonal inhomogeneities in the permeability and storativity fields. The simplified single-phase flow through a porous medium model was used for the proposed approach. This model was matched to the historical values of the development parameters by restoring the fields of the reservoir parameters. Properties fields were reconstructed using a radial basis functions network and a fully connected linear layer. Based on the reconstructed field, interwell connectivity coefficients were calculated, which corresponded qualitatively and quantitatively to the true interwell connectivity coefficients. The predictive characteristics of the proposed approach were evaluated by split the historical dataset into training and test time intervals.</p>","PeriodicalId":46135,"journal":{"name":"Lobachevskii Journal of Mathematics","volume":null,"pages":null},"PeriodicalIF":0.7,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142217085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of the Wavelet Transform in the Analysis of Non-stationary Processes in Aerodynamic Experiments 小波变换在分析空气动力学实验中的非稳态过程中的应用

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Lobachevskii Journal of Mathematics Pub Date : 2024-08-28 DOI: 10.1134/s1995080224602248

O. E. Kirillov

引用次数: 0