Modeling Of Processes Research Articles

Exploring the Potential of Using a Text-Based Game to Inform Simulation Models of Risky Migration Decisions

Background In this paper, we explore the potential of games to collect empirical data for informing agent-based simulation models of migration. To examine the usefulness of game-based approaches, we conducted a simple, yet carefully designed psychological experiment. Methods In a preregistered study, we used a novel, immersive experimental setting to investigate the risky migration decisions made by migrants and non-migrants. Participants (284 migrants and 284 non-migrants) played a choice-based interactive fiction game—a fully text-based game where players progress by selecting from a list of possible actions—that involved making three risky migration decisions. In one condition, participants were shown a non-linear progress bar and explicit acknowledgements of the choices they made to promote perceived agency: the feeling that one’s actions have a non-trivial impact on the game. In the other condition, the progress bar was linear, and the explicit acknowledgements were omitted. Results Our experimental manipulation was successful; participants in the former condition self-reported higher perceived agency than participants in the latter condition, as did migrants compared to non-migrants. Nevertheless, condition and migrant status did not meaningfully affect the risky migration decisions participants made in the game. Conclusion These findings indicate that the results of generic studies on risky migration decisions conducted on non-migrants can potentially inform simulation models of migration. However, these findings were obtained from a single experiment, and thus warrant replication and further research before definitive conclusions can be drawn. Furthermore, a simple text-based game may be too superficial to allow deep insights into the idiosyncrasies of migration decision-making. This suggests a possible trade-off between clear interpretability of the results and the usefulness for informing simulation models of complex social processes, such as migration.

Interval Type-2 Fuzzy Neural Network Based on Active Semi-Supervised Learning for Non-Stationary Industrial Processes

Accurate models ensure the efficient and safe operations of industrial processes. However, modeling of industrial processes with non-stationary characteristic is challenging. In this study, an interval type-2 fuzzy neural network (IT2FNN) based on active semi-supervised learning (ASSL-IT2FNN) is proposed for such industrial processes. First, an IT2FNN with adaptive fuzzy membership function (FMF) and hierarchical learning method is utilized to achieve considerable modeling accuracy and efficiency. Second, to better tackle with the non-stationary characteristic, an unsupervised distribution detection method is proposed to identify the occurrence moments of concept drift actively from the perspective of probability and spatial projection. Then, by an active semi-supervised learning method, the concept drift samples with partial labels are used to build a subnetwork, guaranteeing the performance of the constructed IT2FNN models with incomplete data in non-stationary environments. Finally, the proposed ASSL-IT2FNN is verified by benchmark simulations and real industrial data, and the experimental results demonstrate its outperformance. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Concept drift is an important indicator of a non-stationary environment. It manifests as changes in the distribution of samples over time, which may reduce the accuracy of models constructed based on historical samples. This study aims to alleviate the impact of concept drift on model performance in non-stationary industrial processes while reduce the cost of sample labeling. By using the adaptive FMF and hierarchical learning method, the designed IT2FNN can effectively deal with the inherent nonlinearity of complicated industrial processes. The samples representing concept drift are actively identified by the Kullback-Leibler (KL) divergence and maximum mean difference (MMD), enabling timely detections of concept drift moments in unsupervised situations. The active semi-supervised learning is used to adapt the constructed model to handle the concept drift, wherein a subnetwork is designed based on concept drift samples and similar historical samples.

Multirate Mixture Probability Principal Component Analysis for Process Monitoring in Multimode Processes

In the multirate sampling processes, the process data are usually collected from various operating conditions and display multimodal characteristics. To monitor these multirate multimode processes, a multirate mixture probability principal component analysis model is proposed for process modeling and fault detection. In this model, the local multirate models are built first for each mode and all of them are subsequently fused with the mixture modeling approach. Such model is able to deal with multirate data with various amount of sampling rates, contributing to a remarkable fault detection and mode identification performance by utilizing all the available measurements even if some variables are unobserved. Then the expectation <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula> maximum algorithm is utilized to estimate all the model parameters in the probabilistic framework and the corresponding monitoring method is also developed based on the constructed models. Finally, the effectiveness of the proposed method is demonstrated through a PRONTO benchmark and a real multimode ammonia synthesis process. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Motivated by the practical problem of ununiform sampling intervals in multimode processes, this paper proposes a novel multirate mixture probability principle component analysis model for processes modeling and monitoring. In this model, all the available observations with different sampling rates can be incorporated, which contributes greatly to capturing the multimodal characteristics within the industrial processes. Such ability is the key to realize multimode process monitoring, evaluation, fault diagnosis, and process optimization. In addition, although this paper only focuses on the continuous multirate data in industry, it is equally applicable to other forms of multirate data, such as images and videos.

Исследования математических моделей процессов деформаций зданий и сооружений

Purpose. The article is aimed at analyzing changes in the dynamic characteristics of a building and establishing the dependence of shear deformation accelerations on the building's storey to predict the effect of seismic vibrations on the technical condition of the building, taking into account the engineering and geological properties of the foundation. Methodology. A number of instrumental observations using geodetic devices, automated monitoring systems and engineering seismic stations were made to study the issues of assessing changes in the dynamic characteristics of high-rise buildings and structures. To create mathematical models of deformation processes of buildings and structures, the study of interaction of structural elements of the building with the engineering-geological structure of the ground in the upper and lower parts of the megapolis was proposed. Findings. The results on ground shaking intensity acceleration, effective duration, spectral coefficients and periods of spectrum maximum are obtained. The results of measurements of vibrations on different floors of a high-rise building based on instrumental records of seismic station of local and distant earthquake have been obtained. Dependences of accelerations of shear deformations on the floor of the building with regard to engineering-geological properties of the base have been established. Predictive models of deformation processes of the building taking into account dynamic characteristics of ground vibrations and energy class of earth crust movements have been proposed. Originality. The analytical technique of correlation analysis of random variables is proposed, by means of which normally distributed linear and nonlinear processes are studied to create a mathematical model of deformation processes of buildings of different storeys. Practical value. The obtained results of the study of deformation processes of buildings and their structural elements allow to predict the dynamic model of the process of displacements of points of the structure taking into account the dynamic characteristics of ground vibrations and energy class movements of the Earth's crust

Features of Engineering Methods of Research Results on Butt Welding on Metal Pipelines

This article discusses the use of flash butt welding (FBW) for increased labor productivity in pipeline construction. However, despite its promise, FBW technologies and equipment have limitations in creating defectfree welded joints. The Ishikawa diagram is used to systematize and analyze factors that cause defects, which are then ranked on a Pareto diagram. The main causes of defects are found to be associated with human factors, such as the qualifications of workers, as well as imperfections in machinery and equipment, material deviations, and technology and measurement limitations. A correlation matrix is used to analyze the causes of the decrease in quality and determine that improving methods and means of FBW processes, along with FBW technologies, is the solution. However, a complete computer model of FBW processes has not yet been created due to difficulties in describing energy release and other energy phenomena. A physical and mathematical model is necessary to take into account energy processes in the welding zone.

Активни деривационни процеси при съществителните в руската реч, насочена към децата

Colloquial Russian has a rich set of productive derivation patterns used in informal registers directed to children, other relatives, friends or pets. This paper considers the most frequent patterns in child directed speech (CDS), such as diminutives (knižka  book-Dim, pesenka  song-Dim) and hypocorostics (Saša  Alexander, Nataša  Natalia). The paper is based on the analysis of the speech of parents from two longitudinal speech corpora of one girl and one boy from 2 to 3 years old. Their mothers demonstrated some differences in their use of derivatives concerning their preferences (mostly diminutives or hypocoristics – types или в tokens) and frequency. Most derivatives used by both mothers served as models for the important derivational processes: suffix rivalry with the same stem (hypocoristics) and adding one and the same suffixes to different stems (diminutive formation). Since the differences between literary Bulgarian and Russian in this sphere have been already described by several authors it would be interesting to compare the frequency of diminutives and hypocoristics in CDS for both languages.

APPLICATION OF THE SAMUELSON EQUATION TO THE EVANS MODEL

Mathematical modeling of economic processes is an actual direction of research, because the well-being of citizens and the country as a whole depends on it. In the case of the market, the prices of most goods and services are not planned centrally, are not directly regulated by the state, but are freely set and changed by the market itself. The main factors that control the movement of prices in the market are the demand and supply of goods. In the economy, the most important are dynamic models, the parameters of which change over time. The Evans model (Walras-Evans-Samuelson model) is currently one of the basic concepts explaining the dynamic establishment of the equilibrium price in the market of one product under the influence of supply and demand. This is due to the fact that knowing the dynamics of the economic parameter we are interested in, we can try to build a forecast of its further evolution. The article examines the market of one product. For convenience, we will assume that the functions of the dependence of demand and supply on the price are given by linear relationships. The construction of the Evans model is that the change in price is directly proportional to the excess of demand over supply and the duration of this excess. The Samuelson differential equation with an initial condition, that is, the Cauchy problem, is obtained. Samuelson's equation has a stationary (equilibrium) point, which is a positive price at which supply and demand will be equal. The analysis of the obtained solution of the problem shows that over a long enough time (relatively speaking, at ) the price asymptotically approaches the equilibrium value. If we are not interested in the temporal dependence, but only in the equilibrium price, then it can be found from the differential equation immediately by setting the condition , this is the so-called limit stationary mode. The solution of the Cauchy problem is found by the method of variation of the constant. The parameterization of the model using the fractional differentiation operator in the sense of Gerasimov-Caputo is considered. The resulting solution was analyzed depending on the parameter . For this, the asymptotic representation of the function was used for large values of the argument. Conclusions are made regarding price dynamics in time relative to the equilibrium price when demand and supply are equal.

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.

Review of the Modelling of Corrosion Processes and Lifetime Prediction for HLW/SF Containers—Part 1: Process Models

The disposal of high-level radioactive waste (HLW) and spent nuclear fuel (SF) presents a unique challenge for the prediction of the long-term performance of corrodible structures since HLW/SF containers are expected, in some cases, to have lifetimes of one million years or longer. Various empirical and deterministic models have been developed over the past 45 years for making predictions of long-term corrosion behaviour, including models for uniform and localised corrosion, environmentally assisted cracking, microbiologically influenced corrosion, and radiation-induced corrosion. More recently, fracture-mechanics-based approaches have been developed to account for joint mechanical–corrosion degradation modes. Regardless of whether empirical or deterministic models are used, it is essential to be able to demonstrate a thorough mechanistic understanding of the corrosion processes involved. In addition to process models focused on specific corrosion mechanisms, there is also a need for performance-assessment models as part of the overall demonstration of the safety of a deep geological repository. Performance-assessment models are discussed in Part 2 of this review.

Computer modeling of digestive processes in the alimentary tract and their physiological regulation mechanisms: closing the gap between digestion models and in vivo behavior.

A model has been developed for in silico simulation of digestion and its physiological feedback mechanisms. The model is based on known physiology described in the literature and is able to describe the complexity of many simultaneous processes related to food digestion. Despite the early stage of development of the model, it already encompasses a large number of processes that occur simultaneously, enabling the prediction of a large number of post-prandial physiological markers, which can be highly functional in combination with in vitro, organ-on-a-chip and digital twin models purposed to measure the physiological properties of organs and to predict the effect of adjusted food composition in normal and diseased states. Input from and collaboration between science fileds is needed to further develop and refine the model and to connect with in vitro, in vivo, and ex vivo (organ-on-a-chip) models.

Uncertainty dynamics in energy planning models: An autoregressive and Markov chain modeling approach

This paper deals with the modeling of stochastic processes in long-term multi-stage energy planning problems when limited information is available about the distributions of such processes. Starting from simple estimates of variation intervals for uncertain parameters, such as energy demands and costs, we model the temporal correlation of these parameters through carefully constructed autoregressive (AR) models that respect the intervals defined in each period. We introduce a coefficient for “zigzag” effects in the evolution of uncertain processes, which controls the correlation across periods and also the likelihood of extreme scenarios. To preserve the convexity of the stochastic problem, we discretize the AR models associated with the cost parameters involved in the objective function by Markov chains. The resulting formulation is then solved using a Stochastic Dual Dynamic Programming (SDDP) algorithm available in the literature that handles finite-state Markov chains. Our numerical experiments, carried out on the Swiss energy system, show a very desirable adaptation strategy of investment decisions to uncertainty scenarios, a behavior that is not observed when the temporal correlation is ignored. Moreover, the solutions lead to better out-of-sample cost performances, especially on extreme scenario realizations, than the non-correlated ones which usually result in overcapacities to protect against high, but unlikely, parameter variations over time.

The higher-order analysis of response for linear structure under non-Gaussian stochastic excitations with known statistical moments and power spectral density

The frequency-domain analysis method is a fundamental component of the random vibration analysis, in which the corresponding moment spectrum of excitations are the prerequisite. Nevertheless, the determination of the higher-order moment spectra for non-Gaussian stochastic excitations continues to pose a significant challenge in the existing research works. This paper introduces an accurate and efficient computational approach for determining higher-order moment spectra of non-Gaussian stochastic excitations with known statistical moments and power spectral density (PSD). Firstly, following the idea of the simulation method of non-Gaussian stochastic processes, the transformation model between the stationary non-Gaussian stochastic process and underlying Gaussian stochastic process is determined based on the known statistical moments, the PSD of the underlying Gaussian stochastic process is determined using the transformation model. Secondly, the approximate higher-order moment spectra models of stationary non-Gaussian stochastic processes are presented by the PSD of the underlying Gaussian process. Subsequently, the higher-order moment spectra models of non-Gaussian excitations are utilized to compute the higher-order moment spectra of response for the linear structure via the auxiliary harmonic excitation generalized method. Finally, three numerical examples are examined to assess the efficiency and accuracy of the proposed approximate models for the higher-order moment spectra of non-Gaussian stochastic processes.

Determining the minimum required cooling time of profiled assemblies at the Armenian Nuclear Power Plant taking into account the load schedule

Determining the minimum required cooling time of profiled assemblies at the Armenian Nuclear Power Plant, taking into account the load schedule, is an analytical process to establish the shortest required period during which profiled assemblies used in the nuclear power plant energy process must remain in active use. This process considers factors related to changes in the electrical load on the station during different periods. Within the scope of this definition, an analysis of the technical characteristics of profiled assemblies is conducted as well as their impact on the overall performance of the nuclear power plant. Key considerations in the cooling time include operational safety, compliance with regulatory requirements, and efficient distribution of energy resources in accordance with the load schedule. The goal of this process is to ensure optimal and safe operation of profiled assemblies, adapted to changes in the electrical grid and aligned with the load schedule, thereby contributing to the more efficient functioning of the nuclear power plant. This study aims to substantiate the minimum required cooling time for profiled nuclear assemblies characterized by an average uranium enrichment of 3.82% and an average burnup of 45.7 Megawatt-days per kilogram of uranium (MWD/kgU). Calculations are performed using the ORIGEN-ARP program, part of the SCALE software package designed for the analysis and modeling of radioactive and nuclear processes. The study considers parameters such as the composition of nuclear assemblies, fuel burnup, modeling using the ORIGEN-ARP program, and safety analysis. The results obtained aim to make a significant contribution to enhancing the efficiency and safety of nuclear energy installations

Simulating vacuum arc initiation by coupling emission, heating and plasma processes

Vacuum arcing poses significant challenges for high-field vacuum devices, underscoring the importance of understanding it for their efficient design. A detailed description of the physical mechanisms involved in vacuum arcing is yet to be achieved, despite extensive research. In this work, we further develop the modeling of the physical processes involved in the initiation of vacuum arcing, starting from field emission and leading to plasma onset. Our model concurrently combines particle-in-cell with Monte Carlo collisions (PIC-MCC) simulations of plasma processes with finite element-based calculations of electron emission and the associated thermal effects. Including the processes of evaporation, impact ionization and direct field ionization allowed us to observe the dynamics of plasma buildup from an initially cold cathode surface. We simulated a static nanotip at various local fields to study the thresholds for thermal runaway and plasma initiation, identifying the significance of various interactions. We found that direct field ionization of neutrals has a significant effect at high fields on the order of 10 GV/m. Furthermore, we find that cathode surface interactions such as evaporation, sputtering and bombardment heating play a major role in the initiation of vacuum arcs. Consequently, the inclusion of these interactions in vacuum arc simulations is imperative.

Результаты научных исследований Брянского государственного университета в 2023 году в сфере развития канатных технологий для различных отраслей экономики

The article presents the results of research activities in 2023 by scientists of the Academician I.G. Petrovskii Bryansk State University in the field of developing promising domestic designs of single-span mobile ropeways of various designs — based on autonomous self-propelled wheeled chassis with high load capacity and cross-country ability and based on modular airmobile units. The results of the creation of scientifically based methods for their design and computer modeling of operational processes are also presented. The article describes the results of the creation of a theory of design and modeling of work processes for harvesters equipped with rope anchoring equipment for logging operations when working on steep slopes in highly rugged or mountainous terrain.

MODELING OF CARBIDE FORMATION IN ALLOY OF THE Ni-Cr-Co-W-Mo-Al-Ti-C SYSTEM

Theoretical modeling of thermodynamic processes of separation of carbide phases was carried out, as well as a practical study of the structure and distribution of chemical elements in carbides. Based on an integrated approach for the Ni-Cr-Co-W-Mo-Al-Ti-C system, new regression models were obtained that make it possible to predict the chemical composition of carbides based on the chemical composition of the alloy. A comparative assessment of the calculation results obtained using regression models and experimental data obtained by X-ray spectroscopy was carried out.

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.

Mechatronic automatic control system of electropneumatic manipulator

Mechatronic systems of electropneumatic automation are one of the main classes of industrial automation systems. A laboratory stand for the study of the mechatronic system of automatic control of the pneumatic manipulator and a computer model for preliminary experiments on the adjustment of the automatic control system were developed. Manual and software control modes are provided for research of indicators of safety and quality of management in both modes. To implement the software control mode, a microcontroller part of the laboratory stand based on ADuC841 was developed, with the help of which it is possible to simulate a part of a certain technological process, to detect and eliminate faults in the automatic control system. A study of automatic control systems using a traditional relay-contactor control system, based on GrafCet technology and using a virtual controller. The combination of computer modeling of technological processes and physical modeling of executive mechanisms is a kind of digital double that displays its state, parameters and behavior in real time. The use of a laboratory stand in combination with an adequate simulation model reduces the complexity of developing control systems for practical applications, and also contributes to the formation of students' creative component, ability to analyze the results, and make decisions in unusual situations, which will increase their theoretical and practical training. The study of mechatronic systems of pneumatic manipulators will allow to increase their efficiency and productivity, to optimize their speed and accuracy for various applications in production. The interaction of mechatronic systems of pneumatic manipulators with other technologies, such as machine learning, artificial intelligence, IoT is the basis for creating more integrated and intelligent systems.

Automated disassembly of e-waste-requirements on modeling of processes and product states.

Automated disassembly is increasingly in focus for Recycling, Re-use, and Remanufacturing (Re-X) activities. Trends in digitalization, in particular digital twin (DT) technologies and the digital product passport, as well as recently proposed European legislation such as the Net Zero and the Critical materials Acts will accelerate digitalization of product documentation and factory processes. In this contribution we look beyond these activities by discussing digital information for stakeholders at the Re-X segment of the value-chain. Furthermore, we present an approach to automated product disassembly based on different levels of available product information. The challenges for automated disassembly and the subsequent requirements on modeling of disassembly processes and product states for electronic waste are examined. The authors use a top-down (e.g., review of existing standards and process definitions) methodology to define an initial data model for disassembly processes. An additional bottom-up approach, whereby 5 exemplary electronics products were manually disassembled, was employed to analyze the efficacy of the initial data model and to offer improvements. This paper reports on our suggested informal data models for automatic electronics disassembly and the associated robotic skills.

Migration barriers for diffusion of As and P atoms in InP and InAs via vacancies and interstitial atoms

Processes of diffusion of As and P atoms in InP and InAs, and atomic and energy structure of group-V vacancies and interstitial P and As atoms in InP and InAs have been investigated using density functional theory. Formation energies of group-V vacancies in InP and InAs and P and As interstitial atoms in InP and InAs have been calculated with hybrid functional. The main types of migration jumps have been determined, and the energy favorable migration paths and migration barriers of As and P atoms diffusion in InP and InAs via vacancies and interstitial atoms have been calculated using climbing image nudged elastic band method. In the case of diffusion of As and P atoms in InP and InAs via interstitial atoms the diffusion process occurs via indirect interstitial mechanism. The migration energy barriers for the vacancy diffusion mechanism are 1.5–2.0 eV, the migration energy barriers for the interstitialcy mechanism are 0.3–0.6 eV. The interstitial atoms have higher formation energies compared to the formation energies of the vacancies, and total activation energies of the diffusion are comparable for the vacancy and interstitialcy mechanisms. The obtained results will be useful for modeling of the diffusion processes in semiconductor structures based on InP and InAs.