Modeling Of Physical Processes Research Articles

Influence of Rolling Resistance and Particle Size Distribution in the Simulation of Sand Infiltration into the Static Gravel Bed

Fine sediment infiltration and subsequent clogging in a gravel bed affect several fluvial, ecological, and biological processes, resulting in the degradation of the river ecosystem. Despite many experimental and a few numerical studies, the process is yet to be entirely understood. We employed a pure Lagrangian framework, called the Discrete Element Method (DEM), to numerically investigate the infiltration process. Special attention is given to tackling the issue of non-spherical and irregular particle shapes and particle size distributions (PSDs) in numerical simulations. Due to computational limitations, these aspects were either not considered or simplified in previous numerical studies. We implicitly included non-spherical and irregular shape effects through rolling resistance models, which do not cause excessive computational overhead. Our study shows that rolling resistance models greatly influence packing and fine sediment infiltration. However, they may also lead to unphysical particle behavior; thus, they should be carefully used in numerical simulations. Oversimplified PSDs do not mirror natural systems, and full PSDs pose computational challenges. Sufficient grain classes are needed to mimic the non-homogeneity and poly-dispersity found in natural fluvial sediments. The infiltrating characteristics of sand concerning PSD and shape effects are linked to size ratio D15,Gravel/D85,Sand, assuring physical and realistic modeling of the infiltration process.

Mathematical understanding (hermeneutic aspects of educational activities)

The article discusses the issues of mathematical understanding as an educational practice of identifying the algorithmic meanings of mathematical (mathematized) educational texts. The hermeneutic orientation towards following the “guiding thread of language” (G.-G. Gadamer), as it is shown, cannot be narrowed to the attitude towards natural languages inherent in humanitarian educational practices. The “common place” of mathematical understanding in educational practices is: some of created languages (of scientific communication) being consolidated around the mathematical installation are not reducible to its sign universality or educational generalizations. But it often turns out to be outside the field of view of practicing teachers, in a didactically abstract position. The article substantiates the possibility of rehabilitating the hermeneutic attitude in mathematical education in connection with its development and strengthening in understanding the prerequisites for the algorithmic solution of mathematical problems (the need for additional information, non-standard solution techniques, transfer of educational goal setting to the area of interdisciplinary relationships or life experience, etc.). The author shows and comments on the effectiveness of the hermeneutic approach in mathematics education using examples of solving problems in algebra, geometry and in constructing mathematical models of various physical processes.

Evaluation of influence of thermoplastic slurry flow conditions on heat transfer coefficient during beryllium ceramic formation

The article presents the results of calculation of the influence of thermoplastic slurry flow conditions on the total heat transfer coefficient when forming ceramic products. Methods of detailed description of casting processes and thermal calculations have been developed to ensure reliable correspondence of calculated data and experimental results implemented on the basis of calculational experiment. The modeling of physical processes occurring during the formation of products allows you to discover new opportunities for improving the quality of castings by allowing you to more closely track the change in the temperature-phase fields of the process and clearly present the solidification kinetics depending on the casting modes. The speed of heat removal from the casting during the solidification period determines the rate of movement of the slurry, along with the temperature field on which the width of the transition region depends. These factors have a direct influence on the formation of the structure of beryllium ceramics. The study of the heat exchange process in the formation of ceramic products depending on temperature, heat at phase transition is the main task, since they largely determine the technological and operational characteristics of beryllium ceramics. The design data allows to determine the optimal conditions of the ceramic casting process and to obtain a solidified product with a uniform structure at the outlet.

Physics-informed neural network simulation of two-phase flow in heterogeneous and fractured porous media

Physics-informed neural networks (PINNs) have received great attention as a promising paradigm for forward, inverse, and surrogate modeling of various physical processes with limited or no labeled data. However, PINNs are rarely used to predict two-phase flow in heterogeneous and fractured porous media, which is critical to lots of subsurface applications, due to the significant challenges in their training. In this work, we present an Enriched Physics-Informed Neural Network (E-PINN) to overcome these barriers and realize the simulation of such flow. Specifically, the Embedded Discrete Fracture Model (EDFM) is adopted to explicitly represent fractures, and then the finite volume method (FVM) instead of the Automatic Differentiation (AD) is used to evaluate spatial derivatives and construct the physics-informed loss function, so that the flux continuity between neighboring elements with different properties (e.g. matrix and fracture) can be defined rigorously. Besides, we develop a novel physics-informed neural network (NN) architecture adopting the adjacency-location anchoring, adaptive activation function, skip connection and gated updating to enrich the pressure information and enhance the learning ability of NN. Additionally, the initial and boundary conditions are constrained through a hard approach, which encodes them into network design, to improve the accuracy and efficiency of network training. In order to further reduce the difficulty of training, the Implicit-Pressure Explicit-Saturation (IMPES) scheme is used to calculate pressure and saturation, in which only the pressure needs to be solved by training NN. Finally, the superiority and applicability of E-PINN to complex practical problems is demonstrated through the simulations of immiscible displacement in 2D/3D heterogeneous and fractured reservoirs.

BASES OF THE METHOD OF PHYSICAL MODELING OF THE PROCESS OF CRUSHING OF MUNICIPAL SOLID WASTE

A large number of studies are aimed at increasing the energy efficiency of grinding processes of various solid materials, while maintaining the values ​​of other important indicators, such as material consumption, productivity, etc. Based on this trend, a new method for physically modeling the process of grinding municipal solid waste (MSW) was proposed for the first time. Existing physical modeling techniques are designed for homogeneous and isotropic materials (for example, soil, crushed stone, snow, coal, etc.). The strength properties of solid waste vary widely due to the significant heterogeneity of their components. Consequently, when crushing solid waste, traditional crusher designs have low efficiency in terms of energy intensity, material intensity and product quality. The purpose of this work is to develop a new technique for physical modeling of the grinding process, based on the main principles of similarity theory and modeling, considering the properties of waste heterogeneity. As a result of the research, a block diagram of the physical modeling methodology for the interaction of the working bodies of impact crushing machines with solid waste was developed. A list of tasks for the modeling process and similarity criteria have been determined based on the development of rheological models of the “working body - municipal solid waste” system and the laws of mechanics that characterize the waste grinding process. Based on the developed similarity criteria, scale equations for the grinding process are substantiated and formulas are derived for determining the expected parameters of the original based on the parameters measured on the model. The developed methodology makes it possible to create a crusher design with improved energy efficiency indicators with the least material and labor costs.

Challenges and directions for digital twin implementation in otorhinolaryngology.

Digital twin technology heralds a transformative era in Otorhinolaryngology (ORL), merging the physical and digital worlds to offer dynamic, virtual models of physical entities or processes. These models, capable of simulating, predicting, and optimizing real-world counterparts, are evolving from static replicas to intelligent, adaptive systems. Fueled by advancements in communication, sensor technology, big data analytics, Internet of Things (IoT), and simulation technologies, artificial intelligence (AI), digital twins in ORL promise personalized treatment planning, virtual experimentation, and therapeutic intervention optimization. Despite their potential, the integration of digital twins in ORL faces challenges including data privacy and security, data integration and interoperability, computational demands, model validation and accuracy, ethical and regulatory considerations, patient engagement, and cost and accessibility issues. Overcoming these challenges requires robust data protection measures, seamless data integration, substantial computational resources, rigorous validation studies, ethical transparency, patient education, and making the technology accessible and affordable. Looking ahead, the future of digital twins in ORL is bright, with advancements in AI and machine learning, omics data integration, real-time monitoring, virtual clinical trials, patient empowerment, seamless healthcare integration, longitudinal data analysis, and collaborative research. These developments promise to refine diagnostic and treatment strategies, enhance patient care, and facilitate more efficient and tailored ORL research, ultimately leading to more effective and personalized ORL management.

Development and preliminary validation of a land surface image assimilation system based on the Common Land Model

Abstract. Data assimilation is an essential approach to improve the predictions of land surface models. Due to the characteristics of single-column models, assimilation of land surface information has mostly focused on improving the assimilation of single-point variables. However, land surface variables affect short-term climate more through large-scale anomalous forcing, so it is indispensable to pay attention to the accuracy of the anomalous spatial structure of land surface variables. In this study, a land surface image assimilation system capable of optimizing the spatial structure of the background field is constructed by introducing the curvelet analysis method and taking the similarity of image structure as a weak constraint. The fifth-generation ECMWF Reanalysis – Land (ERA5-Land) soil moisture reanalysis data are used as ideal observation for the preliminary effectiveness validation of the image assimilation system. The results show that the new image assimilation system is able to absorb the spatial-structure information of the observed data well and has a remarkable ability to adjust the spatial structure of soil moisture in the land model. The spatial correlation coefficient between the model surface soil moisture and observation increased from 0.39 to about 0.67 after assimilation. By assimilating the surface soil moisture data and combining these with the model physical processes, the image assimilation system can also gradually improve the spatial structure of soil moisture content at a depth of 7–28 cm, with the spatial correlation coefficient between the model soil moisture and observation increased from 0.35 to about 0.57. The forecast results show that the positive assimilation effect could be maintained for more than 30 d. The results of this study adequately demonstrate the application potential of image assimilation system in short-term climate prediction.

Experimental study of a thin thermally grown oxide layer in thermal barrier coatings based on the SWT-BP algorithm and terahertz technology

As a promising nondestructive testing (NDT) technique with a very adaptive physical modeling of wave transmission process, terahertz technology is used for the detection and characterization of nonpolar materials and the evaluation of layered and/or defective structures. THz-TDS can also be used to perform spectroscopic analysis and detect structural defects in thermal barrier coatings (TBCs) of aero-engines. Although it is generally difficult to measure the structure of the thin oxide layer of the thermal barrier coatings whose thickness is generally lower than 30 µm (the current axial resolution of the THz-TDS cannot exceed 30 µm). We were able to complete the detection of the oxide layer within 1–29 µm through simulation by using the SWT-BP algorithm. In this study, the analysis was performed on real-world samples, the fitting degree of the SWT-BP algorithm reached 0.77, and the minimum prediction error was less than 0.1 µm. The paper also put forward some improvement measures about the experimental results.

Nonlinear dynamics and optimal control strategies of a novel fractional-order lumpy skin disease model

Fractional order differential equations are often employed to better and accurately model several natural and physical processes with memory characteristics than the integer-order models. In this work, a proposed fractional-order model is presented to simulate one of the most dangerous viral cattle diseases. The present fractional-order Lumpy Skin Disease model considers the interactions between different compartments of cattle and virus vectors. The solution of the model is examined in terms of existence, uniqueness, positivity and boundedness. Then, the stability analysis of the different equilibrium points in the model is carried out. The basic reproduction number, R0, has been obtained too. The dependence of stability regions on the values of key parameters is demonstrated and the sensitivity of R0 to different parameters in the system is also investigated. Finally, a proposed optimal control scheme is adopted to successfully diminish the disease spread. It is found that the stability of disease-free equilibrium point is verified at small values of the infection rate of cattle caused by infected cattle or insects. In addition, the disease-free equilibrium point maintains its stability in cases where the recovery rate of cattle or the vaccination rate of cattle are increased. Moreover, the high-efficiency vaccination program helps in stabilizing the disease-free equilibrium point. Also, the fractional-order parameter is found to provide additional degree of freedom in the model to represent different scenarios of evolution for solution orbits. The optimal control parameters of the model are examined in different scenarios to limit or suppress the spread of the disease. It is demonstrated that two control parameters are sufficient to achieve the goals of disease elimination and stabilization of an infection-free steady state. Numerical simulations are verified to confirm our theoretical findings and estimations.

Mathematical modeling of the creation process and aging of polymer composite materials

Based on the analysis of the literature on the possibility of using neural networks to create new materials with high functional properties, the article considers a solution to the problem of determining the operational stability of polymeric composite materials by creating physical and chemically sound mathematical prediction models. Epoxy resins of the UP-637 and EA brands with an isophorone diamine hardener were chosen as the matrix of the model composite material, and oligobutadiene rubber of the SKN-10 KTR brand was chosen as the modifier. It justifies directions of work necessary for development of new materials creation methodology with optimal characteristics, building a model for changing the properties of materials at variation of composition and implementation of full-scale mathematical modeling of physical and chemical processes of polymer composite materials aging at changing level and time of climatic factors influence. Verification of the obtained dependence of service characteristics on the composition of the material and the level of influencing climatic factors was carried out on the basis of data from full-scale tests in a temperate climate. The proposed methodology for modelling the properties of polymer composite materials will reduce the development time of new materials and allow creation of polymer composites based on epoxy resin containing fillers of various natures (carbon, mineral and polymer) with high performance parameters.

On the behaviors of solutions of a nonlinear diffusion system with a source and nonlinear boundary conditions

We study the global solvability and unsolvability of a nonlinear diffusion system with nonlinear boundary conditions in the case of slow diffusion. We obtain the critical exponent of the Fujita type and the critical global existence exponent, which plays a significant part in analyzing the qualitative characteristics of nonlinear models of reaction-diffusion, heat transfer, filtration, and other physical, chemical, and biological processes. In the global solvability case, the key components of the asymptotic solutions are obtained. Iterative methods, which quickly converge to the exact solution while maintaining the qualitative characteristics of the nonlinear processes under study, are known to require the presence of an appropriate initial approximation. This presents a significant challenge for the numerical solution of nonlinear problems. A successful selection of initial approximations allows for the resolution of this challenge, which depends on the value of the numerical parameters of the equation, which are primarily in the computations recommended using an asymptotic formula. Using the asymptotics of self-similar solutions as the initial approximation for the iterative process, numerical calculations and analysis of the results are carried out. The outcomes of numerical experiments demonstrate that the results are in excellent accord with the physics of the process under consideration of the nonlinear diffusion system.

OBTAINING THE NECESSARY MECHANICAL PROPERTIES OF BLANKS OF PARTS MADE OF ALUMINUM ALLOY 7075 BY PHYSICAL MODELING

The article considers physical modeling for aluminum alloy 7075, widely used in mechanical engineering, in particular for elements of aircraft structures. This alloy differs from other rolled aluminum-based alloys not only by high values of strength properties, but also by the presence of a large number of intermetallic compounds of alloying elements. The workpiece for the parts is a round rolled product with regulated mechanical properties. Thus, the purpose of this work was to determine the effect of the deformation pattern that occurs in metal during bar rolling on the mechanical properties of blanks of parts made of aluminum alloy 7075. The present study draws attention to the importance of physical modeling in determining the characteristics of materials necessary for effective management of plastic processing processes. Analyzing the results of physical modeling, we identify the optimal parameters of material processing, such as microstructure, mechanical properties and chemical composition. The results obtained allow a deeper understanding of the physical mechanisms underlying the production of blanks (rods) from aluminum rods of alloy 7075 by rolling, as well as optimizing it to achieve the required technical characteristics of products. Thus, as a result of physical modeling of the rolling process of bars made of aluminum alloy 7075, it was found that when the samples are deformed at a temperature of 250 ° C, the value of the plasticizing stress decreases by about 18%, and a more uniform distribution of microhardness over the transverse and longitudinal sections was obtained compared with deformation at a temperature of 200 °C. The research is of practical importance for the metalworking industry, and can also be used for educational purposes to train specialists in the field of materials science and metalworking. Keywords: workpiece parts, physical modeling, aluminum alloy 7075, metalworking, aluminum alloy microstructure, deformation of samples.

Comparative analysis of two-dimensional and three-dimensional modeling of heat transfer during operation of a gas infrared heater indoor

Relevance. It is proposed to heat local work areas with systems based on gas infrared heaters, capable of directing radiative heat flow to reduce heating costs in large premises. However, the widespread use of gas infrared heaters is hampered by the existing difficulties with the preliminary assessment of convective-radiative heat flows movement, on which the number and location of heating devices depends. The preliminary assessment is complicated by the need in some cases for 3D modeling of complex physical processes. It is necessary to evaluate the possibility of replacing labor-intensive 3D modeling with a method for calculating a heating system using gas infrared emitters based on a 2D approach to reduce the time spent on calculations. Aim. To prove that the use of a two-dimensional model of the processes under consideration makes it possible to obtain the main characteristics of the thermal regime of the premises, making it possible to replace spatial modeling. Objects. Heating system with a light-type gas infrared heater and an air exchange system. Methods. Two-dimensional and three-dimensional mathematical modeling of conjugate heat transfer processes using the finite element method. Mathematical modeling was carried out in the COMSOL Multiphysics software environment using the modules: “Heat Transfer Interface in Liquids”, “Radiation between Surfaces” and “Turbulent Flow, k-ε Interface”. Results. The article presents the results of mathematical modeling performed in three-dimensional and two-dimensional formulations. The distribution of temperatures in the air and enclosing structures, as well as the flow lines of heated air and air, which was heating, in the volume of the premise are presented. The results of two-dimensional and three-dimensional modeling were compared. Satisfactory similarity of the calculated average air temperatures in the local working area was established based on the results. The difference was less than 2℃ for different spatial modeling approaches.

Release potential, neglected leakage and reduction countermeasures of COD and Ammonia in MSWLs

In order to eliminate the impact of the industrial revolution on the environment and improve the water ecological environment, pollutant discharge reduction is imperative. With the acceleration of global discharge reduction process, the huge pollutant release potential and potential environmental effects of municipal solid waste landfills gradually appear, but its release amount and intensity have not been quantitatively revealed. We propose a coupling method of parameter stochastic simulation and physical process model simulation to estimate the hidden leakage of large-scale regional municipal solid waste landfills, and provide a methodology for estimating the hidden leakage of landfills in other countries and even in the whole world by taking China, which has the largest amount of waste generation among developing countries, as an example. Prior to the implementation of stringent construction quality control and assurance management requirements, the average annual leachate generation potential over the entire life cycle of 2600 landfills in China was estimated to be 4.66 × 108 m3, in which the concentrations of COD and NH3-N are 5.38 × 102–6.48 × 104 mg/L and 6.10–3.50 × 103 mg/L, respectively, and the total amounts are 5.21 × 103–7.81 × 108 t and 8.09 × 102–6.65 × 107 t, respectively. About 14 % of these pollutants may leak into the environmental media through the landfill liner with the average number of holes of 21.5/ha. For different regions, the overall release, discharge and leakage of COD and NH3-N in East China account for 35.70 %, 36.68 % and 29.60 % respectively, making it the region with the highest potential for discharge and risk of leakage. Meanwhile, the implementation of mandatory regulations related to leachate generation and control has led to a significant reduction in the leakage of pollutants. For instance, comprehensively detecting and repair of holes in the impermeable liner has reduced the number of holes to 2/ha, resulting in a reduction of >90 % in the leakage of pollutants.

Agent-based risk modeling of domino effects in urban LNG stations

As the transfer hub between natural gas and users, urban LNG stations (ULSs) are the important link of the whole LNG industry chain. Due to special geographical location and various process equipment, potential risks in ULSs, especially domino effect accidents, usually lead to catastrophic consequences and social impacts. In this study, a dynamic risk assessment model for analyzing domino effects in urban LNG stations (DRADL) based on agent modelling and simulation is proposed. Tanks and tank cars as well as vaporizers and boilers in ULSs are modeled. A set of physical process and effect models are employed as the simulation process in this paper. Considering the lightweight nature and narrow flammability limit of LNG vapor cloud, a cyclic process is applied to judge the consequences of vapor cloud dispersion, which could avoid overestimating the results. A real urban LNG station is taken as a case study for modeling its potential domino effect risk. The results demonstrate the effectiveness and the advantages of the proposed ABMS approach for LNG dynamic risk assessment. The proposed DRADL model takes into account the combined effects of explosion and fire and LNG characteristics, which can provide guidance for risk management and rescue operation of domino effect accidents in urban LNG stations.

Research on Prediction Model of Particulate Matter in Dalian Street Canyon

In urban areas where populations commonly reside, particle mass concentrations in street canyons can pose significant risks to human health. This study aimed to investigate the diffusion mechanism of particle mass concentrations in urban street canyons by developing and applying a prediction model based on the mathematical modeling of physical processes. The prediction model considered factors such as the influence of traffic wind, natural wind, traffic flow, and other relevant variables influencing particle mass concentrations in street canyons. Field measurements were conducted in Dalian, China, to verify the feasibility of the model. Particle mass concentrations, traffic flow, temperature, relative humidity, and wind speed were measured on Shichang Street (a two-lane one-way road), Tangshan Street (a four-lane two-way road), and Shengli Road (a six-lane two-way road). The results indicated that the majority of traffic peaks occurred around 19:00 on all road types. The PM1.0 mass concentration was well diluted on the four-lane two-way road, with the least dilution observed on the two-lane one-way road. A strong correlation between the particle mass concentrations and traffic flow was discovered. Furthermore, a prediction model was established, accurately predicting the particle mass concentrations when the prediction step was from 5 to 15 s. The coefficient of determination (R2) between the predicted and measured values on the two-lane one-way road, four-lane two-way road, and six-lane two-way road was 0.9319, 0.6582, and 0.9238, respectively. Additionally, the prediction model allowed for a detailed analysis of traffic flow limitations, corresponding to the recommended World Health Organization (WHO) PM2.5 values. Overall, the findings of this study offer valuable insights for forecasting particle exposure levels in street canyons.

Assessment and Ensemble-Based Analysis of the Landfalling Typhoon Muifa (2022)

By considering the uncertainties in the initial field, model physical processes, and lateral boundary conditions, the Shanghai Weather And Risk Model System-Ensemble Prediction System (SWARMS-EN) is constructed. According to the prediction results of typhoon Muifa (2022), the daily track error of SWARMS-EN within 5 days is 70.6 km, 142.2 km, 129.1 km, 174.5 km, and 203.5 km, respectively. When compared with the Typhoon Ensemble Data Assimilation and Prediction System (TEDAPS) and the Global Ensemble Forecast System (GEFS) of the National Centers for Environmental Prediction (NCEP) in homogeneous conditions, SWARMS-EN performs better than TEDAPS within 72 h and better than GEFS beyond 72 h in track forecasting. This indicates an improvement in forecasting accuracy. The ensemble spread within two days is less than the root mean square error (RMSE), according to an analysis of the relationship between ensemble RMSE and spread, which shows that SWARMS-EN has no apparent systematic bias overall. The system has improved the ensemble RMSE and spread, indicating that it can better represent the uncertainty of the forecast and produce more reliable forecasts. Additionally, SWARMS-EN provides the landfall forecast five days in advance. The ensemble-based analysis suggests that the large-scale circulation is the primary factor contributing to the forecast differences among members, and the strong steering flow provides an indication of the landfalling forecast. The analysis of the ensemble characteristics of the initial field indicates that the initial perturbation between the wind field and the temperature field in the dynamically unstable region (such as near a tropical cyclone) exhibits flow dependence, and the small perturbation shows continuity throughout the entire troposphere. The distribution of ensemble spread and disturbance energy exhibited a reasonable growth stage as the forecast lead time increased. Disturbance internal energy dominated the lower troposphere, while the upper troposphere was mainly characterized by disturbance kinetic energy. Disturbance kinetic energy played a leading role in the evolution process. This conclusion further confirms the importance of paying attention to the initial small perturbations near TC in order to optimize the initial perturbation.

Changes in filtration and capacitance properties of highly porous reservoir in underground gas storage: CT-based and geomechanical modeling

The paper presents the results of comprehensive studies of filtration and capacitance properties of highly porous reservoir rocks of the aquifer of an underground gas storage facility. The geomechanical part of the research included studying the dependence of rock permeability on the stress-strain state in the vicinity of the wells, and physical modeling of the implementation of the method of increasing the permeability of the wellbore zone - the method of directional unloading of the reservoir. The digital part of the research included computed tomography (CT)-based computer analysis of the internal structure, pore space characteristics, and filtration properties before and after the tests. According to the results of physical modeling of deformation and filtration processes, it is found that the permeability of rocks before fracture depends on the stress-strain state insignificantly, and this influence is reversible. However, when downhole pressure reaches 7-8 MPa, macrocracks in the rock begin to grow, accompanied by irreversible permeability increase. Porosity, geodesic tortuosity and permeability values were obtained based on digital studies and numerical modeling. A weak degree of transversal anisotropy of the filtration properties of rocks was detected. Based on the analysis of pore size distribution, pressure field and flow velocities, high homogeneity and connectivity of the rock pore space is shown. The absence of pronounced changes in pore space characteristics and pore permeability after non-uniform triaxial loading rocks was shown. On the basis of geometrical analysis of pore space, the reasons for weak permeability anisotropy were identified. The filtration-capacitance properties obtained from the digital analysis showed very good agreement with the results of field and laboratory measurements. The physical modeling has confirmed the efficiency of application of the directional unloading method for the reservoir under study. The necessary parameters of its application were calculated: bottomhole geometry, stage of operation, stresses and pressure drawdown value.

Teaching the asynchronous general physics course in a crisis context: a case study at Igor Sikorsky Kyiv Polytechnic Institute

The imposition of martial law and power outages in Ukraine made the first semester of the 2022/2023 academic year at Igor Sikorsky Kyiv Polytechnic Institute a challenge for lecturers and students, especially in learning the general physics course. An asynchronous learning mode became the only possible form in such a situation, so the problem of increasing the efficiency of conducting a lecture, problem sessions, and laboratory work in general physics arose. This study aims to describe the implementation of the discipline of general physics (part 1) promoted in an asynchronous mode by lecturers of the Department of General Physics and Modeling of Physical Processes. We verified that in crisis conditions, it is essential to: (i) provide students with all the necessary material on Moodle course and YouTube channel, allowing them to learn the theoretical material, solve the homework problems, and analyse the data from laboratory work, (ii) give feedback and consultations to students via Zoom/Telegram chat upon request, (iii) give the possibility to perform the laboratory work both in the virtual regime and as YouTube demonstration. The results of the survey of 82 students who studied the general physics course taking into account the recommendations mentioned above revealed that the majority of the surveyed students were completely/to a greater extent satisfied with the level of organisation of asynchronous learning, as well as the level of knowledge obtained, which undoubtedly indicates the effectiveness and efficiency of the proposed approach.

A theory of stochastic fluvial landscape evolution

Geometries of eroding landscapes contain important information about geologic, climatic, biotic and geomorphic processes. They are also characterized by variability, which makes disentangling their origins challenging. Observations and physical models of fluvial processes, which set the pace of erosion on most continents, emphasize complexity and variability. By contrast, the spectral content of longitudinal river profiles and similarity of geometries at scales greater than approximately 100 km highlight relatively simple emergent properties. A general challenge then, addressed in this manuscript, is development of a theory of landscape evolution that embraces such scale-dependent insights. We do so by incorporating randomness and probability into a theory of fluvial erosion. First, we explore the use of stochastic differential equations of the Langevin type, and the Fokker–Planck equation, for predicting migration of erosional fronts. Second, analytical approaches incorporating distributions of driving forces, critical thresholds and associated proxies are developed. Finally, a linear programming approach is introduced, that, at its core, treats evolution of longitudinal profiles as a Markovian stochastic problem. The theory is developed essentially from first principles and incorporates physics governing fluvial erosion. We explore predictions of this theory, including the natural growth of discontinuities and scale-dependent evolution, including local complexity and emergent simplicity.