Modeling Of Physical Processes Research Articles

ON PROBLEM OF PROPERTIES OPTIMIZING FOR VISCOELASTIC MATERIALS USING THE BEGLEY-TORVIK EQUATION

Recently, fractional calculus has been the focus of attention of many researchers in the field of science and technology, since a more detailed study of physical processes leads to the need to complicate the mathematical models that describe them, and, consequently, to the study of the behavior of solutions of differential equations containing, along with " ordinary", or "classical", derivative, also fractional. Processes of this kind can include: studies of continuous media with memory, fluid filtration in media with fractal geometry, physical aspects of stochastic transfer and diffusion, mathematical models of a viscoelastic body, models of damped oscillations with fractional damping (for example, vibrations of rocks during earth-quakes or vibrations nanoscale sensors), models of non-local physical processes and phenomena of a fractal nature; climate models, etc. The paper studies boundary value problems for the equation of motion of an oscillator with viscoelastic damping (the Begley-Torvik equation) in the case when the damping order is greater than zero but less than two. Such problems model many physical processes, in particular, the vibration of a string in a viscous medium, the change in the deformation-strength characteristics of polymer concrete under loading, etc. This paper is devoted to optimizing the parametric control of the Begley-Torvik model. A fundamentally new, efficient algorithm is proposed that allows estimating the parameters of a model of real material.

Combination of Snow Process Model Priors and Site Representativeness Evaluation to Improve the Global Snow Depth Retrieval Based on Passive Microwaves

The spatiotemporal distribution of snow depth (SD) has a significant impact on the energy and water balances of the Earth’s system. However, passive microwave remote sensing widely used for SD estimation has large uncertainties due to the variations in snow physical properties. In this study, we demonstrate a new method to minimize these uncertainties and to increase the accuracy of SD estimation. Our method is based on the synergy between the passive microwave AMSR-2 brightness temperature (TB) and a physical snow process model (SNTHERM) to estimate snow grain size, snow density and first-guess SD as priors. On one hand, we used TB from three frequencies and removed non-representative ground measurements at the stations to improve deep snow estimation. Then, we applied a machine learning (ML) algorithm based on both the AMSR-2 TB and the SNTHERM simulations to retrieve the global SD. The results showed that the root-mean-squared error (RMSE) of the retrieved SD was 12.4 cm at the meteorological stations. Independent validations showed that our method significantly reduced the SD and snow water equivalent (SWE) underestimation in the mountains compared to the current satellite products.

Implementation of Yang residual power series method to solve fractional non-linear systems

<abstract><p>In this study, we implemented the Yang residual power series (YRPS) methodology, a unique analytical treatment method, to estimate the solutions of a non-linear system of fractional partial differential equations. The RPS approach and the Yang transform are togethered in the YRPS method. The suggested approach to handle fractional systems is explained along with its application. With fewer calculations and greater accuracy, the limit idea is used to solve it in Yang space to produce the YRPS solution for the proposed systems. The benefit of the new method is that it requires less computation to get a power series form solution, whose coefficients should be established in a series of algebraic steps. Two attractive initial value problems were used to test the technique's applicability and performance. The behaviour of the approximative solutions is numerically and visually discussed, along with the effect of fraction order $ \varsigma $. It was observed that the proposed method's approximations and exact solutions were completely in good agreement. The YRPS approach results highlight and show that the approach may be utilized to a variety of fractional models of physical processes easily and with analytical efficiency.</p></abstract>

МЕТОДИКА РАСЧЕТА ОЗОНАТОРА СОТОВОЙ СТРУКТУРЫ

Relevance The use of ozone-catalytic reactions is a promising method for purifying water, air and exhaust gases. They can be used, among other things, to solve the problem of cold starting of a car engine, allowing for the effective neutralization of toxic impurities even at low temperatures. Optimization of an ozone-catalytic device (according to the criterion of minimizing specific energy costs) requires the development of a mathematical model that takes into account the mutual influence of numerous parameters of physical processes occurring in the channels of the catalytic unit. A large number of mutually influencing parameters actualizes the use of iterative algorithms for the numerical solution of a system of equations of a mathematical model. Aim of research The aim of this article is to develop a mathematical model of the physical processes occurring in the ozonizer, and to create on its basis an iterative method that is possible to determine the change in temperature, pressure and composition of the gas mixture as it moves through the channels of the ozonizer of a honeycomb structure, taking into account the mutual influence of these parameters to each other and to the power of the barrier discharge. Research objects Ozone catalytic device. Research methods Mathematical modeling of physical processes. Results To solve the system of equations describing the physical processes in the ozone-catalytic device, an iterative algorithm was developed to determine the spatial distribution of parameters (temperature, pressure, ozone concentration) in the channels of the catalytic unit of the honeycomb structure.

Training simulators for crane operators and drivers

The article deals with the use issues of modern information technology for training purposes. In particular, use of simulation modelling to create a learning environment as close as possible to the real working environment. This helps speed up learning, make more practical, learn theoretical issues directly when mastering practical skills, and make the learning process more attractive and interesting for students. Moreover, a virtual working environment can be used for advanced training of employees, to improve their professional skills, master new technologies, train them to work on new and modernized equipment, assess their professional level, restore skills after a long break in the work and pass qualification exams. Information technologies can significantly reduce the cost of material support for training and eliminate dependence on large areas for staff training. To create an interactive virtual learning environment, modern gaming technologies, software modelling or, at least, simulation modelling of physical processes in equipment and the interaction of all components of the working environment, including the actions of the student, are used. It also allows testing employees in extreme working conditions and testing their skills when dealing with non standard and emergency situations, without any real danger to the health of students. The proposed solution can be used to train students and trainees, assess professional skills of those already working in the conditions of special training centers and professional retraining colleges.

ВЛИЯНИЕ ЧАСТОТЫ ПИТАЮЩЕГО НАПРЯЖЕНИЯ НА ЭФФЕКТИВНОСТЬ ОБРАЗОВАНИЯ ОЗОНА В ОЗОНАТОРЕ СОТОВОЙ СТРУКТУРЫ

Relevance A promising direction for the development of domestic and foreign eIn the modern world, more and more attention is paid to environmental issues. One of the effective ways to solve environmental problems is the use of ozone - an allotropic modification of oxygen, which has high oxidizing abilities and can be used to purify and sterilize water, air and exhaust gases. However, the spread of technologies related to the use of ozone is hampered by their energy intensity. In this regard, an urgent task is to optimize the design of ozonizers and its power supply mode to reduce the specific energy consumption for ozone production. The main aim The aim of this article is to study the dependence of the efficiency of ozone formation on the frequency of the supply voltage and to determine the optimal frequency at which this efficiency would reach its maximum value. Research objects Ozonizer. Research methods Mathematical modeling of physical processes. Results An expression is obtained to determine the distribution of the electric field strength in the discharge gap. An iterative algorithm has been developed, as a result of which graphs of the dependence of the critical frequency value on the amplitude of the supply voltage, as well as on the temperature and pressure of the gas passing through the discharge gap, are obtaine

Computer modeling of physical phenomena

This article presents aspects of the use of Information Technology in physics lessons, in particular, the work of students with computer models. This work helps to increase students ' interest in studying the subject and the level of thinking. Topic relevance the use of computer models of various physical processes and phenomena contributes to the effectiveness of teaching physics to students, allowing them to understand the mechanisms of physical phenomena, often invisible to the human eye, and in some cases impractical and impossible in life. In order to identify the advantages of computer modeling, studies were conducted on two groups of 9th grade students (Control and experimental), their general understanding in the use of computer modeling was studied, and the role of computer modeling in understanding the concepts of speed and acceleration in body movement was determined. The two groups were applied the same traditional type of training on this topic, and the peculiarity was that the experimental group used computer simulations as a complement. Based on the results presented in the studies, it is shown that students working with the help of computer modeling scored significantly higher scores in their tasks. After analyzing the results, it is confirmed that computer modeling can be used as an additional teaching tool that helps to increase the level of thinking of students, as well as to develop systemic ideas about phenomena in physics. In the course of research using modeling, on average, 6 out of 10 students achieved good results. The importance of teaching using computer models, organizing the student's interaction with the model to participate in active research activities is revealed. It was also found that computer models can be used both in distance learning and in traditional learning, including with network support. The result of the research is that the training of physics teachers in computer modeling can be used internationally in the training of future physics teachers, enhancing their intellectual abilities, contributing to the performance of mental operations and the development of intelligence in general.

Editorial: Advances in observations and modeling of physical processes in the marine environment

Editorial: Advances in observations and modeling of physical processes in the marine environment

Physical Modeling of Positive Multistrike Lightning Formation

The first results of the physical modeling of positive multistrike lightning formation processes using positively charged artificial thunderstorm cells are presented. Experimental studies have shown a significant influence of the number of thunderstorm cells and groups of model hydrometeors introduced into them on the probability of the initiation of repeated strikes. It was found that with an increased number of cells and groups of model hydrometeors, the probability of the formation of repeated positive discharges increases several times. When the second group of model hydrometeors has been introduced into the artificial thunderstorm cell, or when the number of cells has been increased, the probability of the repeated discharge initiation has increased almost in three and in four times respectively. It has been revealed that, depending on the arrangement of model hydrometeor groups in artificial thundercloud cells, the formation of repeated positive discharges from them may proceed both with the “connection” of the uncharged areas of the lower cell and with the “connection” of the upper cell. The parameters of the first and repeated impulse current pulses between the positively charged cells and the ground were determined. It was found that with an increasing number of model hydrometeor groups, the value of the charge neutralized during the stages of first and repeated discharge formation increases. When forming multistrike positive discharges with the “connection” of the upper artificial thunderstorm cell, 20–30% more cloud charge has been neutralized during the repeated discharge than during the formation of a single positive discharge. It was found that the formation of positive repeated discharges was observed in about half of the cases, and that the radiation power and impulse current amplitude at repeated discharges are higher than at the first discharge. This article discusses some possible reasons for such a ratio between the parameters of the first and repeated discharges. It is assumed that the discovered significant influence of large model hydrometeor groups on the probability of the formation and the characteristics of repeated positive discharges from artificial thunderstorm cells indicate a possible key influence of hail arrays in the thundercloud on the formation of repeated strikes of positive lightning and bipolar lightning. The obtained results show that artificial thunderstorm cells of positive polarity, together with groups of large model hydrometeors, have prospects for physical modeling and the investigation of processes of the formation of positive and bipolar repeated lightning strikes.

Innovative methods and technologies while examining equations of mathematical physics

Teaching disciplines of physics and mathematics in the age of information technology requires innovative teaching methods application. These methods complement traditional forms; they are aimed at developing the systematic and creative thinking of students. The disciplines of the physical and mathematical profile include such discipline as “Equations of Mathematical Physics”. They help students develop skills in creating mathematical models of physical processes and phenomena. It is advisable to apply software packages to create computer models of situational problems when studying the discipline “Equations of Mathematical Physics”. The mathematical packages application makes it possible to take various situations by changing the input parameters of the model on the basis of computer models of physical processes. The problems of mathematical physics are based on the study of the second-order partial differential equations of three main types: hyperbolic, elliptic, and parabolic. The paper discusses the mathematical package MathCad application in the study of free and forced vibrations of a string. Mathematical models of free and forced oscillations are presented. The d’Alembert formula for solving equations of hyperbolic type is presented. The authors describe stages of the study of free vibrations of the membrane in MathCad. Bessel functions are constructed. Membrane surface animation has been created. Observations of membrane vibrations were carried out.

Mastering the production of special types of pipes made of ferritic-martensitic steels, taking into account the peculiarities of the microstructure and properties

The main results of the development of a technology for the production of special types of pipe products, carried out taking into account the features of the microstructure, the laws of phase and structural transformations, as well as the resistance to plastic deformation in a wide temperature range of steels of the ferritic-martensitic class of grades EP450-Sh and EP823-Sh, are presented. The microstructure was studied with determination of the grain size, the content of non-metallic inclusions and fraction of the main structural components depending on the heating temperature for quenching. Using the Gleeble 3800 multifunctional complex, the resistance to fracture deformation at high temperatures was determined. In the laboratory of JSC RusNITI, physical modeling of the cold rolling process in a two-roll stand was carried out according to the oval-oval calibration scheme in the mode of successive increase in reduction. On the basis of the studies carried out for the steel grades under study, were developed the modes for pressing stock hot-pressed pipes with dimensions of 133.0×14.0 and 89.0×7.0 mm; cold rolling of both large-scale samples of round pipes and stock pipes intended for subsequent production of hexagonal pipes; final heat treatment of pipes of round and hexagonal sections, ensuring compliance with the requirements of technical specifications. As part of the project direction, PJSC TMK developed and implemented, through inter-plant cooperation with JSC VTZ, TMK-INOKS Ltd. and JSC RusNITI, a new technology for manufacturing hexagonal pipes according to the hot pressing – cold deformation scheme (rolling, profiling), whereby large-scale samples of new types of pipes for special purposes were obtained from EP450-Sh and EP823-Sh steel grades. The results obtained are used to form a set of technical requirements for the new type of high-tech pipe products, presented in technical specifications TU 420-2021, TU 422-2021, TU 423–2021.

DTCO flow for air spacer generation and its impact on power and performance at N7

A novel DTCO flow is described with the principal aim to study the impact of air spacer fabrication on the power and performance of a 5-stage inverter ring oscillator at the 7 nm node. The flow incorporates physical and analytical process models from the in-house ViennaPS simulation tool together with device and circuit simulations from GTS Framework’s Cell Designer. The air spacer is usually filled by sequential conformal and non-conformal deposition steps. The impact of the thickness of the conformal layer and the sticking probability during non-conformal deposition on the ring oscillator performance is studied here. The air gap, which forms the core of the air spacer, is generated during the non-conformal deposition step. We extract the relative effective permittivity of the air spacer as a function of these two fabrication parameters by solving the Poisson equation to obtain the spacer capacitance. Finally, SPICE model cards are extracted automatically from the TCAD transistor characteristics and the parasitic network is calculated from the full 3D ring oscillator logic cell using a field solver. We apply our framework on two fabrication flows, when the air gap is created before and after the deposition of the first metal contacts layer. We observe that introducing the air gap inside the spacer results in an at-least 15% improvement in the ring oscillator’s performance, when the power is kept constant. Further improvements can be achieved by reducing the conformal layer thickness and increasing the sticking probability by increasing the chamber partial pressure or increasing the process temperature.

A Method for Forest Canopy Height Inversion Based on Machine Learning and Feature Mining Using UAVSAR

The mapping of tropical rainforest forest structure parameters plays an important role in biodiversity and carbon stock estimation. The current mechanism models based on PolInSAR for forest height inversion (e.g., the RVoG model) are physical process models, and realistic conditions for model parameterization are often difficult to establish for practical applications, resulting in large forest height estimation errors. As an alternative, machine learning approaches offer the benefit of model simplicity, but these tools provide limited capabilities for interpretation and generalization. To explore the forest height estimation method combining the mechanism model and the empirical model, we utilized UAVSAR multi-baseline PolInSAR L-band data from the AfriSAR project and propose a solution of a mechanism model combined with machine learning. In this paper, two mechanism models were used as controls, the RVoG three-phase method and the RVoG phase-coherence amplitude method. The vertical structure parameters of the forest obtained from the mechanism model were used as the independent variables of the machine learning model. Random forest (RF) and partial least squares (PLS) regression models were used to invert the forest canopy height. Results show that the inversion accuracy of the machine learning method, combined with the mechanism model, is significantly better than that of the single-mechanism model method. The most influential independent variables were penetration depth, volume coherence phase center height, coherence separation, and baseline selection. With the precondition that the cumulative contribution of the independent variables was greater than 90%, the number of independent variables in the two study areas was reduced from 19 to 4, and the accuracy of the RF-RVoG-DEP model was higher than that of the PLS-RVoG-DEP model. For the Lope test area, the R2 of the RVoG phase coherence amplitude method is 0.723, the RMSE is 8.583 m, and the model bias is −2.431 m; the R2 of the RVoG three-stage method is 0.775, the RMSE is 7.748, and the bias is 1.120 m, the R2 of the PLS-RVoG-DEP model is 0.850, the RMSE is 6.320 m, and the bias is 0.002 m; and the R2 of the RF-RVoG-DEP model is 0.900, the RMSE is 5.154 m, and the bias is −0.061 m. The results for the Pongara test area are consistent with the pattern for the Lope test area. The combined “fusion model” offers a substantial improvement in forest height estimation from the traditional mechanism modeling method.

A Reliable Way to Deal with the Coupled Fractional Korteweg-De Vries Equations within the Caputo Operator

The development of numeric-analytic solutions and the construction of fractional order mathematical models for practical issues are of the highest concern in a variety of physics, applied mathematics, and engineering applications. The nonlinear Kersten–Krasil’shchik-coupled Korteweg–de Vries-modified Korteweg–de Vries (KdV-mKdV) system is treated analytically in this paper using a unique method, known as the Laplace residual power series (LRPS) approach to find some approximate solutions. The RPS methodology and the Laplace transform operator are combined in the LRPS method. We provide a detailed introduction to the proposed method for dealing with fractional Kersten–Krasil’shchik-linked KdV-mKdV models. When compared to exact solutions, the approach provides analytical solutions with good accuracy. We demonstrate the effectiveness of the current strategy compared to alternative methods for solving nonlinear equations using an illustrative example. The LRPS technique’s results show and highlight that the method may be used for a variety of time-fractional models of physical processes with simplicity and computing effectiveness.

The cold regions hydrological modelling platform for hydrological diagnosis and prediction based on process understanding

Cold regions involve hydrological processes that are not often addressed appropriately in hydrological models. The Cold Regions Hydrological Modelling platform (CRHM) was initially developed in 1998 to assemble and explore the hydrological understanding developed from a series of research basins spanning Canada and international cold regions. Hydrological processes and basin response in cold regions are simulated in a flexible, modular, object-oriented, multiphysics platform. The CRHM platform allows for multiple representations of forcing data interpolation and extrapolation, hydrological model spatial and physical process structures, and parameter values. It is well suited for model falsification, algorithm intercomparison and benchmarking, and has been deployed for basin hydrology diagnosis, prediction, land use change and water quality analysis, climate impact analysis and flood forecasting around the world. This paper describes CRHM’s capabilities, and the insights derived by applying the model in concert with process hydrology research and using the combined information and understanding from research basins to predict hydrological variables, diagnose hydrological change and determine the appropriateness of model structure and parameterisations.

A Hybrid Framework for Rapidly Locating Transition Zones: A Comparison of Event‐ and Response‐Based Return Water Levels in the Suwannee River FL

AbstractFlood risk assessments commonly use event‐based approaches to reduce the number of scenarios required to be run through computationally intensive physical process models. Often the return period of the response variable (e.g., a fluvial water level or overtopping discharge) generated by an event (e.g., upstream/downstream water level or set of sea state variables) does not match that of the event itself; a limitation of event‐based approaches which can lead to the misspecification of flood risk. We present a transferable hybrid statistical‐hydraulic modeling framework for rapidly locating transition zones; river reaches where extreme water levels are driven by both upstream riverine discharge and downstream sea level. Instead of an event‐based approach the framework utilizes a surrogate model to reduce computational expense of the hydraulic model. The surrogate‐based approach allows the empirical estimation of response‐based along‐river return levels from a large number of plausible discharge–coastal still water level events simulated from the statistical model. We assess the robustness of the event‐based approach by comparing the associated return levels with the response‐based return levels. The framework is applied to the Suwannee River in Florida (United States). Three surrogate models are evaluated, highlighting the enhanced ability of non‐linear models to accurately capture discharge‐sea level interactions along the river. The along‐river return levels of the “most‐likely” design event are found to lie within the range of variability of the response‐based return levels for most of the transition zone.

Разработка современного метода расчета тепловой работы камерной нагревательной печи

Experiments are often considered as the way to find rational heating modes at manufacturing enterprises. Unlike experimental methods, modern calculation methods use mathematical modeling of physical and chemical processes in heating furnaces. It allows to reduce the time of the research and it is less resource intensive. A mathematical model is proposed to find rational operation modes of thermal furnaces according to the specified criterion. The model considers the porosity of the heated material and the flow of the furnace atmosphere through it. Finite difference method and the zonal method to calculate complex heat transfer is used for numerical implementation of the model. A mathematical model of the thermal operation of a thermal furnace to heat bulk cages has been developed, considering the filtration of combustion products. The developed mathematical model is designed to find new modes of thermal operation of the heating furnace, which provide a specified quality of the final product with a minimum fuel consumption or maximum furnace productivity according to the given fuel consumption rate.

3D multi-physics uncertainty quantification using physics-based machine learning

Quantitative predictions of the physical state of the Earth’s subsurface are routinely based on numerical solutions of complex coupled partial differential equations together with estimates of the uncertainties in the material parameters. The resulting high-dimensional problems are computationally prohibitive even for state-of-the-art solver solutions. In this study, we introduce a hybrid physics-based machine learning technique, the non-intrusive reduced basis method, to construct reliable, scalable, and interpretable surrogate models. Our approach, to combine physical process models with data-driven machine learning techniques, allows us to overcome limitations specific to each individual component, and it enables us to carry out probabilistic analyses, such as global sensitivity studies and uncertainty quantification for real-case non-linearly coupled physical problems. It additionally provides orders of magnitude computational gain, while maintaining an accuracy higher than measurement errors. Although in this study we use a thermo-hydro-mechanical reservoir application to illustrate these features, all the theory described is equally valid and applicable to a wider range of geoscientific applications.

A comparative experimental study of rill erosion on loess soil and clay loam soil based on a digital close-range photogrammetry technology

Accurately describing rill development is important for building physical process models of soil erosion. The objectives of this study were to investigate the evolution processes of rill erosion morphology, their impacts on runoff and sediment yield, and the relationship between flow hydraulic characteristics and rill erosion dynamic mechanisms on slopes of two soil types, namely, clay loam soil (CLS) and loess soil (LS), under two successive rainfall events at a rainfall intensity of 120 mm h−1. We used digital close range photogrammetry technology to obtain overhead images of two experimental soil bins (5 m long, 1 m wide and 0.5 m deep with a slope gradient of 20°) at 5-minute time intervals to monitor the dynamic processes of rill erosion. The results showed that rill erosion processes exhibited important impacts on sediment and runoff and its hydrodynamic characteristics. Compared with LS, runoff formed and rills developed earlier in the CLS slope. Soil with high clay content was more prone to form rills, but less susceptible to severe soil erosion than LS. Once rills began to develop in LS, soil loss increased and the morphology of rills changed rapidly, as did runoff rate. The flow velocity for the two soils decreased gradually with time and increased along the flow direction. The trend of Froude number (Fr) decreased with time, whereas the Darcy-Weisbach resistance coefficient (f) exhibited an opposite trend. The Reynolds number (Re) of LS increased first and then decreased, while Re of CLS decreased gradually with time. Sediment yield and runoff were positively correlated with f, but significantly negatively correlated with Fr. Moreover, Re was significantly negatively correlated with sediment yield, but not with runoff. These results are of great importance for soil loss prediction.

Inversion of thermal properties of lunar soil from penetration heat of projectile using a 2D axisymmetric model and optimized PSO algorithm

The thermophysical parameters of lunar soil can be inferred from the temperature field during the invasion process of reconnaissance projectile. This paper adopts a two-dimensional axisymmetric model to reconstruct the projectile invasion process. An optimized particle swarm optimization method is then used to retrieve the thermophysical parameters of lunar soil. When the reconnaissance projectile penetrates the lunar interior, it rubs against the lunar soil and generates heat, which diffuses between the projectile body and the lunar soil. The sensors inside the reconnaissance projectile measure the temperature variation of the projectile body to inverse the thermophysical parameters. This paper carried out physical modeling of the penetration process of reconnaissance projectile. A two-dimensional axisymmetric simulation model is constructed for the physical process, and the adaptive inertial weight particle swarm algorithm is adopted. The inversion experiment of lunar soil thermophysical parameters based on the simulation model shows that the inversion error is less than 10%, which verifies the feasibility of this method.