Divergence Problem Research Articles

Efficient hydraulic and thermal simulation model of the multi-phase natural gas production system with variable speed compressors

The natural gas production system is a very complex system, involving pipelines, compressors and valves with different structures and calculation parameters. It can be divided into two different parts: gas production and collection pipe networks. Fluid flow in the gas production pipe network is multi-phase flow. Fluid flow in the gas collection pipe network is single-phase flow. It is imperative to consider gas production and collection pipe networks in conjunction to ensure accurate operation simulation. The complexity of the network structures and flow statuses can cause computational instability or even divergence problems in simulations when coupling these two types of pipe networks. To address this issue, an automatic and practical node numbering method is proposed for the large-scale pipe network, which can ensure the full rank of the solution matrix and computational stability. On the other hand, due to the need for frequent adjustments of the pipe networks to satisfy the production demand, computational boundary treatments of constant inlet/outlet pressure, constant flow rate or constant pressure ratio for the compressor stations are not suitable. To address this issue, the characteristic curves of compressors are coupled into the simulation of pipe networks to represent the variable-speed centrifugal and reciprocating compressors.The accuracy and robustness of the proposed models and numerical methods are validated through comparisons with software results and field data. The simulation time is only within 0.5 s for the natural gas production system with 210 nodes and 176 pipelines. Our model has relative deviations within 3% in both pressure and flow rate compared to field data and within 10% compared to software.

State of charge estimation for lithium-ion battery based on improved online parameters identification and adaptive square root unscented Kalman filter

Accurate state of charge estimation is crucial for the safe and efficient operation of lithium-ion batteries. The Kalman filtering algorithm has been widely used in state-of-charge (SOC) estimation. To solve the problem of filter divergence and sensitivity to noise, the joint SOC estimation method is proposed to achieve accurate and robust estimation of SOC, which is composed of improved variable forgetting factor recursive least square (VFFRLS) and adaptive square root unscented Kalman filter (ASRUKF). The improved VFFRLS method uses the mean square value of the multi-step voltage residual instead of the traditional one-step voltage residual to correct the forgetting factor, and the ASRUKF improves the accuracy and stability of estimation by introducing the square root method and the adaptive method. Estimations under three typical working conditions are quantitatively studied, the experimental results show that the proposed method has good accuracy and stability. The maximum mean absolute error (MAE) is 0.0061, and the corresponding root mean square error (RMSE) is 0.0090. Furthermore, the experimental verification after adding offset errors to measured data shows that the proposed method can still track the reference SOC with satisfactory accuracy in the range of voltage offset error less than ±0.5 % and current offset error less than ±3 %, both for the constant offset error and the random error, and the SOC error is less than 2.5 %.

Birth and death of entanglement between two accelerating Unruh-DeWitt detectors coupled with a scalar field

We study two accelerating Unruh-DeWitt detectors coupled linearly or quadratically with a scalar field, by using an approach different from previous ones. We use Rindler frame, and integrate over the spacetime coordinates before over the momenta. In this way, the divergent problem previously encountered is avoided. We show that entanglement between the detectors can be created by coupling with the field, and is divergent only in the limit that the two detectors coincide in spacetime. For linear coupling, entanglement increases monotonically with the decrease of acceleration, as previously found, while for quadratic coupling, entanglement behaves non-monotonically, as noted for the first time.

Эпистемология противоречий в контексте закона единства и борьбы противоположностей

The problem of divergence of dialectical materialism from the materialist worldview, which causes the necessi-ty of epistemological and ontological comprehension of the known laws of dialectics, is considered. Since the law of transition of quantitative changes into qualitative ones and the law of negation of negation have been considered by the author in previous works, the subject of the study becomes the law of unity and struggle of opposites. The unity and contradictions of the object of cognition are placed in the focus of the research. The unity of the object of cognition is qualified within the framework of the system approach as its integrity, in turn defined through stability and localization. Consideration of contradictions of the object of cognition revealed their division into real and imaginary. Real contradictions are associated with the processes of creation and destruction, underlying the existence of all objects in the world. Imaginary contradictions arise in the process of cognition and include contradictions of unreliability of knowledge, methodological contradictions and termino-logical contradictions. Among the imaginary contradictions also includes the contradiction of identity and differ-ence of the object of cognition.

Continuous data assimilation of large eddy simulation by lattice Boltzmann method and local ensemble transform Kalman filter (LBM-LETKF)

We investigate the applicability of the data assimilation (DA) to large eddy simulations based on the lattice Boltzmann method (LBM). We carry out the observing system simulation experiment of a two-dimensional (2D) forced isotropic turbulence, and examine the DA accuracy of the nudging and the local ensemble transform Kalman filter (LETKF) with spatially sparse and noisy observation data of flow fields. The advantage of the LETKF is that it does not require computing spatial interpolation and/or an inverse problem between the macroscopic variables (the density and the pressure) and the velocity distribution function of the LBM, while the nudging introduces additional models for them. The numerical experiments with grids and 10% observation noise in the velocity showed that the root mean square error of the velocity in the LETKF with observation points ( of the total grids) and 64 ensemble members becomes smaller than the observation noise, while the nudging requires an order of magnitude larger number of observation points to achieve the same accuracy. Another advantage of the LETKF is that it well keeps the amplitude of the energy spectrum, while only the phase error becomes larger with more sparse observation. We also see that a lack of observation data in the LETKF produces a spurious energy injection in high wavenumber regimes, leading to numerical instability. Such numerical instability is known as the catastrophic filter divergence problem, which can be suppressed by increasing the number of ensemble members. From these results, it was shown that the LETKF enables robust and accurate DA for the 2D LBM with sparse and noisy observation data.

The Formalism Issue of Catholic Iconography in China

During the Republican period in China, the Catholic Church gradually developed and grew in China and made attempts to localize itself in different fields, one of which was the promotion of localized Catholic icon painting in the field of art. Due to the problem of divergence between Chinese and Western cultures and styles, formalistic expressions of these paintings emerged. As a representative practice of Catholic painting in China, Beiping Fu Jen Catholic University, with Chinese painting style as its main focus and Western style as its auxiliary, consciously innovated the expression of Catholic icon painting in China, however, in the expression of content and selection of subject matter, excessive emphasis was placed on Chinese visual language to cater to the tastes of Chinese audiences, and as the edifying function of Catholic painting failed to be exercised to a certain extent. There is still a certain degree of formalism. The development of Catholic painting in China needs to find a balance between the spirit of doctrine and Chinese visual culture, integrate Catholic aesthetics into the Chinese painting tradition, and create a new form of painting language, rather than the migration and appropriation of visual symbols.

Проблема дивергенции оценок, присуждаемых лицами, оказывающими услуги по оценке устойчивого развития. Главные тренды в области законодательного регулирования института ESG-рейтингования в России и мире

Confidence in environment, social, and governance (ESG) ratings among investors remains at a fairly low level. An Edelman Insights study [2021] reported that almost three out of four institutional investors do not trust companies to achieve their stated commitments in the fields of sustainability, ESG, or diversity, equity, and inclusivity (DEI). One of the reasons for this distrust is the divergence of ESG ratings – that is, the difference in ratings given by different ESG agencies to the same companies. The origins of this problem lie in the fact that there is still no developed framework to regulate the process of assessing the sustainable development of companies. However, more and more international actors are becoming involved in this issue in order to increase confidence in the assessments of ESG rating providers. For example, codes of conduct for data and ESG ratings providers have already been issued by the United Kingdom (UK), the European Union (EU), India, and Japan. The Central Bank of Russia also issued an information letter on the regulation of the activities of ESG rating providers in the summer of 2023. This article studies the problem ESG ratings’ divergence and determines ways to solve it through the development of regulatory control. It also studies the main trends in the legislative regulation of this institution in order to implement them into the Russian regulatory framework. In this regard, an analysis of work by Russian and foreign researchers devoted to the study of differences in ESG ratings was carried out; additionally, the main approaches of international organizations and legislative bodies of Russia and other countries in the sphere of regulating ESG information providers and mandatory non-financial reporting of companies were studied. The main problems affecting the reduction of ESG data correlation are identified, solutions for them are proposed, and the key trends in improving the comparability of ESG ratings by international actors are noted. The comparative legal method was used in the study. The analysis shows that international actors resolve the problem of divergence by increasing their interpretability, but not through strict regulation. They propose to develop basic recommendations regarding methodologies, evaluation criteria, and weighting factors, while at the same time consolidating the responsibility of ESG rating agencies to disclose their methodology, the terminology used, and their rating definitions. The task is to create harmonized standards for, and transparency of, the ESG assessment process.

Aerodynamics-based forward-swept wing structure optimization

This paper reviews and evaluates the most recent studies on forward-swept wing technology. A number of experimental plans and applications for forward-swept wing aircraft have been produced as a result of the study of forward-swept wings, the investigation of aerodynamic circumstances, and the creation of related designs. The related theories and exposed problems of the forward-swept wing aircraft, such as the problem of aeroelastic divergence, structural strength, and the descent of transonic flight state, are gradually solved. It will be demonstrated that forward-swept wing aircraft have outstanding aerodynamic performance in subsonic flight. In comparison to current aircraft, it may gain more controllability advantages, enhance low-speed controllability, increase aerodynamic efficiency in a variety of flying scenarios, decrease stall speed, making the aircraft less likely to enter the spiral state, and increase safety and dependability. The research in the field of forward swept wing will increase the possibility of successful development and practical use of forward swept wing aircraft.

How combinations of constraint affect creativity: A new typology of creative problem solving in organizations

Research suggests that extreme levels of constraint can push people to use different types of creative problem solving, but this conflicts with recent theory arguing that individuals are most creative under a moderate level of constraint. To resolve this issue, this paper proposes a combinatorial theory of constraints that argues it is necessary to understand how multiple dimensions of constraint (e.g., on problems and resources) work together to influence creativity, rather than study them in isolation. Accordingly, two conditions can enhance creativity—either through divergent problem solving or emergent problem solving—because they produce an overall balanced combination of constraint that improves important psychological mechanisms of creativity such as intrinsic motivation and creative search. Alternatively, two other conditions can hinder creativity—either due to ambiguous opportunity or futile effort—because they produce a combined low or high level of constraint on a task.

Flow and heat transfer in Phan-Thien–Tanner viscoelastic fluid around a rotating hot cylinder in a square enclosure

Flow and heat transfer problems in non-Newtonian fluids are considerably more complicated compared to Newtonian fluids due to their non-linear behavior and complex properties. This paper numerically studied the flow and heat transfer of a viscoelastic fluid around a hot rotating cylinder in a square enclosure. The Phan-Thien–Tanner (PTT) model, one of the most accurate models available to describe the behavior of viscoelastic fluids, was used to obtain the constitutive equations of the viscoelastic fluid, which were then solved by using the finite-volume method with the Rheoheatfoam solver of the OpenFOAM software. The log-conformation approach was employed to avoid the divergence problem at high Weissenberg numbers. Simulations were conducted to investigate the effects of the Weissenberg number, Brinkman number, Reynolds number, and the ratio of the polymeric viscosity to total viscosity on the behavior of fluid flow and heat transfer. The results showed that increasing the Weissenberg number led to a higher shear thinning effect, which decreased the fluid's effective viscosity and viscous dissipation near the cylinder. As a result, heat transfer from the cylinder increased, and the frictional torque applied to the cylinder decreased. However, the shear thinning effect was negligible when the Weissenberg number exceeded 100. Furthermore, the tangential normal stress significantly increased as the Weissenberg number increased up to one. However, with further increases in the Weissenberg number, the tangential normal stress reduced, eventually reaching close to zero at high Weissenberg numbers.

ON SOME APPLICATIONS OF DIVERGENT PROBLEMS

The paper is devoted to identifying possible effective applications of divergent problems in school courses in mathematics and physics. The article first outlines the essence of the divergent task, its contributing role in the formation and development of the logical and creative thinking of students, after which the varieties of divergent tasks are interpreted, and then, for each variety, examples of divergent tasks found in school courses in mathematics and physics are discussed in detail. The first kind of divergent problems are problems that allow different solutions. As an example, this paper discusses one mathematical problem of determining the largest value of an expression. In addition to the standard method, as a means of stimulating the creative abilities of students, three more options for solving the problem are proposed, which, differing significantly from each other, contribute to a comprehensive consideration of the problem. The next problem discussed in the article is from the "Mechanics" section of the school physics course. Three different approaches to solving this problem are presented. At the same time, these approaches differ not so much in mathematical solutions as in the accepted physical ideas. The next type of divergent problems are problems that have ambiguity, freedom or uncertainty in their conditions. The article analyzes in detail the mathematical problem of motion and the non-standard problem of dynamics, as divergent problems of the second type. The study provides guidelines, the use of which will contribute to the search for ways to solve divergent problems, and will allow you to protect as much as possible from mistakes made in the preparation or solution of such problems, which is the scientific and pedagogical novelty of the article

Cognitive FDA-MIMO Radar Network for Target Discrimination and Tracking With Main-Lobe Deceptive Trajectory Interference

This paper propose a cognitive FDA-MIMO radar network (CFDA-MIMON) target discrimination and tracking algorithm under main-lobe deceptive trajectory interference. This algorithm can be divided into two stages: search-discrimination-initialization and cognitive target tracking. The first stage mainly uses the distribution characteristics of target and main-lobe deceptive trajectory interference on different radars to discriminate the target and interference in the radar network. A target state initialization strategy driven by G-pair measurements with large time interval is proposed for target tracking. In the second stage, a cognitive target tracking algorithm of single FDA-MIMO radar system is designed based on the criteria of maximum Capon power spectrum (CMCP). In addition, in order to avoid the divergence problem of the EKF filter, a target state correction method (TSC) based on auxiliary particles is proposed. Finally, the fusion strategy of multiple radar trajectories is used to alleviate the estimation error of the single radar. Numerical experiments verify that the proposed CFDA-MIMON target discrimination and tracking algorithm can distinguish the target from main-lobe deceptive trajectory interference without prior information of the target, and output the target's trajectory.

A discussion on the relativistic corrections of the electronic structures of multi‐electron atoms

AbstractThe theory of special relativity is a topic not addressed in theoretical chemistry courses. Einstein's theory of relativity is mainly applied to high‐energy phenomena governed by physical laws not used to describe the chemical bond. Nevertheless, the electrons of heavy elements orbit around the nucleus with relativistic velocities. Here it is, then, the laws that appeared so unusual for chemistry became fundamental tools for investigating the properties of these atoms. Studying the electronic structure of heavy elements is the best place for chemists to learn to tame the pitfalls of a little‐known subject, such as Einstein's theory, and become familiar with its elegant formalism. In this paper, the main relativistic approaches to quantum chemistry are revisited. The problem of the finite nuclear size, the approximation methods used to solve the relativistic equations for k‐shell electrons, and the problem of the negative energy continuum are investigated. Some ansatzes to solve divergence's problem of relativistic corrections near the nucleus are proposed. Finally, a possible connection between the self‐consistent field method and bondonic chemistry is also investigated.

A deep domain adaptation framework with correlation alignment for EEG-based motor imagery classification

It is impractical to collect sufficient and well-labeled EEG data in Brain-computer interface because of the time-consuming data acquisition and costly annotation. Conventional classification methods reusing EEG data from different subjects and time periods (across domains) significantly decrease the classification accuracy of motor imagery. In this paper, we propose a deep domain adaptation framework with correlation alignment (DDAF-CORAL) to solve the problem of distribution divergence for motor imagery classification across domains. Specifically, a two-stage framework is adopted to extract deep features for raw EEG data. The distribution divergence caused by subjected-related and time-related variations is further minimized by aligning the covariance of the source and target EEG feature distributions. Finally, the classification loss and adaptation loss are optimized simultaneously to achieve sufficient discriminative classification performance and low feature distribution divergence. Extensive experiments on three EEG datasets demonstrate that our proposed method can effectively reduce the distribution divergence between the source and target EEG data. The results show that our proposed method delivers outperformance (an average classification accuracy of 92.9% for within-session, an average kappa value of 0.761 for cross-session, and an average classification accuracy of 83.3% for cross-subject) in two-class classification tasks compared to other state-of-the-art methods.

Repartitioned Brillouin-Wigner perturbation theory with a size-consistent second-order correlation energy.

Second-order Møller-Plesset perturbation theory (MP2) often breaks down catastrophically in small-gap systems, leaving much to be desired in its performance for myriad chemical applications such as noncovalent interactions, thermochemistry, and dative bonding in transition metal complexes. This divergence problem has reignited interest in Brillouin-Wigner perturbation theory (BWPT), which is regular at all orders but lacks size consistency and extensivity, severely limiting its application to chemistry. In this work, we propose an alternative partitioning of the Hamiltonian that leads to a regular BWPT perturbation series that, through the second order, is size-extensive, size-consistent (provided its Hartree-Fock reference is also), and orbital invariant. Our second-order size-consistent Brillouin-Wigner (BW-s2) approach can describe the exact dissociation limit of H2 in a minimal basis set, regardless of the spin polarization of the reference orbitals. More broadly, we find that BW-s2 offers improvements relative to MP2 for covalent bond breaking, noncovalent interaction energies, and metal/organic reaction energies, although rivaling coupled-cluster with single and double substitutions for thermochemical properties.

Ukrainian Architects of the Baroque Age: Algorithms of the Worldview Development

The article raises the problem of the artistic worldviews divergence of the artist (architect) and the commissioner of the construction. It is argued that the problem occurred due to the insufficient influence of aesthetic culture on the educational field in general and in particular, on primary and secondary education. In order to draw corresponding historical parallels, the subject matter of this paper is the Baroque era and the interaction of contemporary architects and commissioners. It is hypothesized that the commonality of artistic worldviews in this tandem was a key reason for its success. Therefore, identifying and investigating the formative factors of a common worldview of the educated circles of the Baroque era may be projected to modern times as an illustrative example of socially relevant architecture. A wide range of approaches was used asthe problem was considered within the axis of“culture—education—society” and in various aspects. The scope of identified factors determined the interdisciplinary nature of the study

Encouraging household energy conservation through transdisciplinary approaches in Ghana and South Africa: assumptions, challenges and guidelines

ABSTRACTTransdisciplinary research has gained traction globally for mapping pathways for sustainable urbanisation. The involvement of local communities is believed to central to knowledge co-production needed to address sustainability challenges. But working with local communities can be challenging. This paper is structured around the authors’ personal reflections on undertaking transdisciplinary household energy conservation projects in Ghana and South Africa. The paper reflects on the assumptions and challenges of doing transdisciplinary research in urban Africa and suggests some guidelines for consideration when doing transdisciplinary projects. An inductive analysis of our reflections showed five key challenges: lack of integration, divergent problem identification, tensions in knowledge co-production, asymmetrical power relations, and distrust and managing expectations. We draw on our collective experiences to develop guidelines for conducting transdisciplinary research in urban Africa. These guidelines are not prescriptive but can be useful for a growing and broader audience interested in undertaking transdisciplinary research.

Blaming it on NATO? Framing the role of NATO in the full-scale Russian invasion of Ukraine on Twitter

IntroductionSince social media has become a significant tool for conflict communication amid the full-scale Russian invasion of Ukraine, researchers have grown more interested in the digital content citizens are exposed to.MethodsTo further investigate the role of social media in the ongoing invasion, we conducted a manual content analysis to examine tweets in English, Russian, and German that explicitly mentioned NATO in the context of the full-scale invasion during February to May 2022. Our analysis explored how these language-specific Twitter communities framed NATO's role in the conflict.ResultsWe found that English-speaking tweeters were more likely to hold NATO responsible for finding a solution and least likely to blame NATO for the war compared to German and Russian speakers. We also observed that the Russian-speaking Twitter community exhibits a comparatively lower tendency to hold NATO accountable for the ongoing war as compared to their German-speaking counterparts, and they are also notably the least likely to expect NATO to bring an end to the war. Finally, English-speaking Twitter users who attribute blame to NATO for the ongoing war tend to adhere to a preconceived notion, rather than arriving at an interpretation based on the situation at hand. This is in contrast to the Russian-speaking community, where the opposite is true. German-speaking users fall somewhere in between these two perspectives.DiscussionOur research contributes to the literature by providing a novel integration of conceptual and methodological perspectives on the framing and stance-taking of social media users during wartime, addressing known research gaps in the comparative analysis of these discussions, i.e., adding “non-English” perspectives. It also highlights the importance of cultural and linguistic sensitivity when addressing responsibility in armed conflicts and the need to consider the diverse perspectives derived from divergent problem definitions and evaluative standards.

AWL-GCN: Branch Parameter Identification Considering Grid Spatial Structure Constraints

Parameter identification plays an important role in power system. The existing parameter identification methods usually have two limitations: (1) The existing methods only consider the information of single branch and ignore the influence of adjacent branch information, and do not effectively use the topological structure constraints of the power grid. (2) The measurement data has the problems of poor numerical stability, numerical divergence and noise interference. Data contamination has become an important factor restricting the prediction accuracy of branch parameters. In order to solve these problems, this work proposes an Automatic Weighted Loss-Graph Convolution Networks model combined with the spatial structure of power grid. Based on the graphical modeling, the correlation between power grid branches is effectively used, and the adjacent branches are used to provide more effective information for the parameter identification of a branch, which improves the identification accuracy. In addition, the model enhances the local characteristics through the power grid structure information constraints, realizes the local optimal fitting, and constructs a self tradeoff loss function to weaken the impact of pollution data (data noise and data loss) on the model. The test results show that compared with the traditional method, this method has higher accuracy and stronger robustness.

New bounds for the empirical robust Kullback-Leibler divergence problem

This paper deals with the bounds of the empirical robust Kullback-Leibler (KL) divergence problem that is proposed in the literature to be used for universal hypothesis testing (UHT). The original problem formulation relies on the bounds derived from the Lévy ball. New bounds are proposed, and they are shown to be more tight. A new parameter is also introduced to be used for modifications of the new and existing bounds. Then, a computational study is devised to evaluate the performance of the modified test in terms of power for fixed sample sizes. Based on the computational results, we can conclude that the new proposals are promising by increasing adaptability of the robust/composite hypothesis testing.