Mesh Nodes Research Articles

Numerical Prediction of Long-Term Droplet Erosion and Washing Efficiency of Axial Compressors Through the Use of a Discrete Mesh Morphing Approach

Abstract Online water washing represents an operation strategy commonly used to reduce compressor performance deterioration due to blade fouling. Since this kind of washing is applied when the machine operates close to full load conditions, injected droplets are strongly accelerated and consequently impact the rotor blades at high velocity, thus inducing undesirable phenomena like erosion. Here, we present a novel technique to study long-term water droplets erosion by also considering the geometry modification caused by droplets impacts. Two-phase unsteady numerical simulations were carried out, considering the injection of water droplets and their transport across the fluid flow in the first part of a real compressor, which is modeled in the region extending from the inlet to the rotor blades of the first stage. Simulations are performed on the whole machine to account for the asymmetric distribution of the spray injectors, the machine struts, inlet guide vanes (IGVs), and rotor blades. The k−ɛ realizable turbulence model with standard wall functions was coupled with the discrete phase model to track injected droplets motion. Droplets-wall interaction is modeled following the Stanton–Rutland approach aiming at detecting the effect of droplet impact (deposit, rebound, and splashing) depending on the impact conditions. Moreover, a semi-empirical erosion model developed by the authors was used to evaluate the erosion induced by the droplets injection. Material removal due to erosion is converted into nodal mesh displacement that is used by a secondary routine to implement the mesh morphing scheme. The mesh modification is applied at discrete steps to reduce the computational load. This technique is adopted to account for the blades geometry modification due to water droplet erosion leading to performance losses. Moreover, an estimation of the compressor operating life before maintenance operations is given and the water washing efficiency during the whole life of the machine is evaluated by means of proper indices. At the end of the simulation workflow, erosion phenomena are observed in all the compressor regions, especially in the rotor where erosion peaks are reached at the hub of the blades leading edge. The rotor blades wet surface was found to remain almost constant at around 50% during compressor water washing. Erosive phenomena were proved to evolve nonlinearly with time indicating the need to account for the geometry modification for obtaining an accurate prediction of the long-time process.

A Hybrid Intelligent Simulation System for Building IoT Networks: Performance Comparison of Different Router Replacement Methods for WMNs Considering Stadium Distribution of IoT Devices.

As the Internet of Things (IoT) devices and applications proliferate, it becomes increasingly important to design robust networks that can continue to meet user demands at a high level. Wireless local area networks (WLANs) can be a good choice as IoT infrastructure when high throughput is required. On the other hand, wireless mesh networks (WMNs), which are WLANs with mesh topology following the IEEE802.11s standard, have many advantages compared to conventional WLANs. Nevertheless, there are some problems that need solutions. One of them is the node placement problem. In this work, we propose and implement a hybrid intelligent system that solves this problem by determining the position of mesh nodes by maximizing the mesh connectivity and the coverage of IoT devices. The system is based on particle swarm optimization (PSO), simulated annealing (SA), and distributed genetic algorithm (DGA). We compare the performance of three router replacement methods: constriction method (CM), random inertia weight method (RIWM), and rational decrement of Vmax method (RDVM). The simulation results show that RIWM achieves better performance compared to CM and RDVM because it achieves the highest connectivity while covering more clients than the other two methods.

The uniform sparse FFT with application to PDEs with random coefficients

We develop the uniform sparse Fast Fourier Transform (usFFT), an efficient, non-intrusive, adaptive algorithm for the solution of elliptic partial differential equations with random coefficients. The algorithm is an adaption of the sparse Fast Fourier Transform (sFFT), a dimension-incremental algorithm, which tries to detect the most important frequencies in a given search domain and therefore adaptively generates a suitable Fourier basis corresponding to the approximately largest Fourier coefficients of the function. The usFFT does this w.r.t. the stochastic domain of the PDE simultaneously for multiple fixed spatial nodes, e.g., nodes of a finite element mesh. The key idea of joining the detected frequency sets in each dimension increment results in a Fourier approximation space, which fits uniformly for all these spatial nodes. This strategy allows for a faster and more efficient computation due to a significantly smaller amount of samples needed, than just using other algorithms, e.g., the sFFT for each spatial node separately. We test the usFFT for different examples using periodic, affine and lognormal random coefficients in the PDE problems.

Local mesh deformation using a dual-restricted radial basis functions method

In order to study the motion of a deformable configuration in the air flow, mesh deformation technology is essentially needed. The radial basis function (RBF) interpolation algorithm is a popular mesh deformation algorithm. For local mesh deformation, such as aeroelastic response simulation of aircraft components and deflection of flight control surface, we do not need to move all grid nodes. On the contrary, only part of the mesh near the deformation boundary needs to be moved. If we can limit the deformation range caused by the RBF method to a small region, the computational cost could be saved. In addition to the consideration of efficiency, another reason is that in the position optimization of aircraft components, we need to keep most of the meshes unchanged to reduce the error caused by mesh inconsistency. In the previous research [24], a restricted RBF interpolation algorithm was constructed and coupled with a multi-level interpolation technique to reduce the volume mesh nodes for global mesh deformation problem. The restricted RBF method is improved in the current research and a so-called dual-restricted RBF algorithm is proposed. This new method constructs a restricting function using the distance both to the moving and static boundaries so that the stationary wall could be preserved exactly. Theoretical analysis and numerical examples also have confirmed that the new algorithm is beneficial to improve the efficiency of mesh deformation process compared with the restricted RBF algorithm because mesh nodes near the stationary boundary no longer need to be moved.

On the Contribution of Wall Distance Fields to the Adjoint of a RANS Model

The adjoint method has been extensively used in many areas of CFD such as gradient-based shape optimisation. When utilising the RANS equations for simulating turbulent flows, the adjoint method requires a scrupulous differentiation of the RANS equations, including the wall distance contribution. This can be a challenging task and a potential source of inaccuracy for functional sensitivities if not correctly executed. This paper presents a formulation for including the contribution of an equation-based wall distance model to the discrete adjoint of a RANS model. The proposed formulation is tested in a gradient-based optimisation scenario and the effects of the wall distance adjoint fields on the functional sensitivities are investigated. Neglecting the contribution of the wall distance adjoint yields an error in the functional sensitivities with respect to volume mesh nodes. Including the wall distance adjoint restores the accuracy of the functional sensitivities yielding better convergence of the design optimisation.

Effects of torso mesh density and electrode distribution on the accuracy of electrocardiographic imaging during atrial fibrillation.

Introduction: Electrocardiographic Imaging (ECGI) allows computing the electrical activity in the heart non-invasively using geometrical information of the patient and multiple body surface signals. In the present study we investigate the influence of the number of nodes of geometrical meshes and recording ECG electrodes distribution to compute ECGI during atrial fibrillation (AF). Methods: Torso meshes from 100 to 2000 nodes heterogeneously and homogeneously distributed were compared. Signals from nine AF realistic mathematical simulations were used for computing the ECGI. Results for each torso mesh were compared with the ECGI computed with a 4,000 nodes reference torso. In addition, real AF recordings from 25 AF patients were used to compute ECGI in torso meshes from 100 to 1,000 nodes. Results were compared with a reference torso of 2000 nodes. Torsos were remeshed either by reducing the number of nodes while maximizing the overall shape preservation and then assigning the location of the electrodes as the closest node in the new mesh or by forcing the remesher to place a node at each electrode location. Correlation coefficients, relative difference measurements and relative difference of dominant frequencies were computed to evaluate the impact on signal morphology of each torso mesh. Results: For remeshed torsos where electrodes match with a geometrical node in the mesh, all mesh densities presented similar results. On the other hand, in torsos with electrodes assigned to closest nodes in remeshed geometries performance metrics were dependent on mesh densities, with correlation coefficients ranging from 0.53 ± 0.06 to 0.92 ± 0.04 in simulations or from 0.42 ± 0.38 to 0.89 ± 0.2 in patients. Dominant frequency relative errors showed the same trend with values from 1.14 ± 0.26 to 0.55 ± 0.21 Hz in simulations and from 0.91 ± 0.56 to 0.45 ± 0.41 Hz in patients. Conclusion: The effect of mesh density in ECGI is minimal when the location of the electrode is preserved as a node in the mesh. Torso meshes constructed without imposing electrodes to constitute nodes in the torso geometry should contain at least 400 nodes homogeneously distributed so that a distance between nodes is below 4 cm.

Dynamic fracture analysis in quasi-brittle materials via a finite element approach based on the combination of the ALE formulation and M−integral method

This work proposes an efficient FE-based approach for reproducing dynamic crack propagation phenomena in quasi-brittle materials. The proposed model uses a Moving Mesh technique based on the Arbitrary Lagrangian-Eulerian formulation (ALE) to adapt the computational mesh consistently to the geometry variations caused by dynamically growing cracks. Specifically, the motion of mesh nodes occurs according to Fracture Mechanics criteria, which provide suitable conditions regarding the direction and velocity of a growing crack tip. These conditions usually depend on the Dynamic Stress Intensity Factors (DSIFs) at the crack front. For extracting the DIFSs at a moving crack tip, this work introduces the ALE formulation of the dynamic M−integral as a key novelty. This strategy offers the key advantage of performing numerical integration procedures on deforming finite elements without losing accuracy. The validity of the proposed method has been assessed through comparisons with experimental and numerical data reported in the literature.

A Parallel Variational Mesh Quality Improvement Method for Tetrahedral Meshes Based on the MMPDE Method

There are numerous large-scale applications requiring mesh adaptivity, e.g., cardiac electrophysiology, computational fluid dynamics, fracture propagation, and weather prediction. Parallel processing is needed for simulations involving large-scale adaptive meshes. In this paper, we propose a parallel variational mesh quality improvement algorithm for use with distributed memory machines. Our parallel method is based on the sequential method by Huang, Ren, and Russell and the recent implementation by Huang and Kamenski. Their approach is based on the use of the Moving Mesh PDE method to adapt the mesh based on the minimization of an energy functional for mesh equidistribution and alignment. This leads to a system of ordinary differential equations (ODEs) to be solved which determine where to move the interior mesh nodes. The MMPDE method successfully removes/reduces the number of extreme dihedral angles, particularly those less than 2 0 o or greater than 15 0 o . An efficient solution is obtained by solving the ODEs on subregions of the mesh with overlapped communication and computation. Strong and weak scaling experiments on up to 128 cores for meshes with up to 160M elements demonstrate excellent results. • A parallel algorithm and implementation are proposed for variational mesh quality improvement on simplicial meshes. This is the first parallel variational mesh quality improvement method. • The method is based on the sequential moving mesh PDE (MMPDE) method of Huang, Ren, and Russell and the recent implementation by Huang and Kamenski which removes or significantly reduces the number of extreme dihedral angles in a tetrahedral mesh upon smoothing. • Their approach adapts the mesh based on the minimization of an energy functional for mesh equidistribution and alignment. This leads to a system of ODEs to be solved for the velocities of the interior mesh nodes. • An efficient solution is obtained by solving the ODEs in parallel on subregions of the mesh with overlapped communication and computation. • Excellent scalability results are obtained on up to 128 cores for tetrahedral meshes with up to 160M elements and on an industrial example from the tire industry.

Mesh generation of complex three‐dimensional geometries for beam‐particle modeling of fracture

AbstractIn this article, we propose a three‐dimensional meshing algorithm for discrete models combining the lattice approach with the polyhedral particle approach. Our aim is to be able to leverage readily available, well‐supported meshers to handle various geometries. We use them to generate a tetrahedral mesh, which our mesher then converts to a polyhedral mesh. The input mesh serves as geometrical support to generate the nodes of the discrete mesh. The desired shape is obtained with an assembly of convex polyhedral particles—without having to clip them. We show that this approach enables meshing convex or concave geometries with sharp edges, curved features, and more. Several three‐dimensional geometries are presented to support this claim and illustrate the capabilities of the mesher. We provide a detailed analysis of its isotropy. The geometric isotropy is studied by analyzing the orientation of the generated beams. The mechanical isotropy is verified by assessing the properties of the elasticity tensor. Finally, we show that the new mesh retains its ability to be a good support for the generation of realistic cracking patterns.

A Random Forest approach to predict geology from geophysics in the Pontiac subprovince, Canada

Current “visual” integration approaches to map geology from geophysics are challenging, biased toward user assumptions, and time consuming. Applying a supervised machine learning Random Forest method to airborne geophysical data sets is an alternative solution to quickly generate interpretative maps, which can later be validated through targeted and therefore more efficient field campaigns. The approach is tested in the Malartic–Cadillac area of the Pontiac subprovince, Canada. Available airborne geophysical data sets include magnetic, frequency-domain electromagnetic, and radiometric data. Unlike the western part of the area, many studies have been done in the eastern part where the world-class Canadian Malartic gold deposit is located. The eastern part has abundant field observations and well-documented geology that are used as training data for Random Forest learning. A predicted map is built after preprocessing the data, gridding the area into a mesh of nodes and training using known geological knowledge. The results provide new information about the spatial distribution of lithological units, including diabase dikes, felsic-intermediate igneous rocks, mafic–ultramafic igneous rocks, and sedimentary rocks. Comparison between the predicted map and previous geological maps could suggest locations where future field mapping efforts should focus in the Malartic–Cadillac area.

A Dual-Radio Hybrid Mesh Topology for Multi-Hop Industrial IoT Networks in Harsh Environments

Industrial Internet of things (IIoT) is a paradigm that changes the way people interact with infrastructures by enabling ubiquitous connection to the Internet. It allows to design connected infrastructures in industrial environments, e.g., factories, in order to support innovative services and improve efficiency. While the advantages of IIoT are numerous, it has some fundamental issues such as propagation of signal through metallic obstacles, i.e., walls in industrial environments. To address this issue, we propose a hybrid wired-wireless mesh node and network topology called hybrid mesh network (HMN), enabling the signal to cross over the metallic obstacles in harsh environments. The proposed hybrid mesh node utilizes dualradio feature of IEEE 802.11 Wi-Fi standard to improve the performance of the proposed HMN further considering multihop communications. The effects of the packet size and different fading channels on the performance of the proposed HMN are investigated through various simulations. In addition, the performance of the proposed HMN is compared with that of conventional wireless mesh network (WMN). The results reveal that the proposed HMN outperforms conventional WMN and the proposed topology is promising for the implementation of high performance wireless mesh networks in harsh environments.

R-adaptive algorithms for supersonic flows with high-order Flux Reconstruction methods

The present paper addresses the development and implementation of the first r-adaptive mesh refinement (r-AMR) algorithm for a high-order Flux Reconstruction solver. The r-refinement consists on nodal re-positioning while keeping the number of mesh nodes and their connectivity frozen. The developed algorithm is based on physics-driven spring-analogies, where the mesh can be seen as a network of fictitious springs. While AMR increases the local mesh density, the high-order Flux Reconstruction method potentially provides a more accurate detection of complex flow features over relatively coarser mesh, when compared to low-order methods. In this work, a concise overview of the Flux Reconstruction method and spring-based AMR techniques will be given, followed by some promising results of r-AMR applied to benchmark high-order steady-state supersonic flow simulations.

A Comparison of Linear Solvers for Resolving Flow in Three‐Dimensional Discrete Fracture Networks

AbstractWe compare various methods for resolving steady flow within three‐dimensional discrete fracture networks, including direct methods, Krylov subspace methods with and without preconditioning, and multi‐grid methods. We compared the performance of the methods based on compute times and scaling of the solution as a function of the number of grid nodes and log‐variance of the hydraulic aperture. The methods are applied to three test cases: (a) variable density of networks with a truncated power‐law distribution of fracture lengths, (b) a fixed network composed of monodisperse fracture sizes but varied permeability/aperture heterogeneity, (c) and a network based on field site in Nevada, US. We chose these cases to allow us to study the impact of the mesh size and flow properties, as well as to demonstrate our conclusions on a large‐scale, realistic problem (more than 40 million mesh nodes). A direct solution using Cholesky factorization outperformed other methods for every example but was closely followed in performance by some algebraic multigrid (AMG) preconditioned Krylov subspace methods. Among the Krylov methods, conjugate gradients (CG) with an AMG preconditioner performs the best. Generally, Cholesky factorization is recommended, but CG with an AMG preconditioner may be suitable for very large problems beyond 40 million nodes where the entire linear system cannot reside in memory.

An Arbitrary Lagrangian–Eulerian Formulation of Two-Dimensional Viscoelastic Beams Based on the Consistent Corotational Method

Abstract In this paper, an arbitrary Lagrangian–Eulerian (ALE) formulation based on the consistent corotational method is presented for the geometric nonlinear dynamic analysis of two-dimensional (2D) viscoelastic beams. In the ALE description, mesh nodes can be moved in some arbitrarily specified way, which is convenient for investigating problems with moving boundaries and loads. By introducing a corotational frame, the rigid-body motion of an element can be removed. Then, the pure deformation and the deformation rate of the element can be measured in the local frame. This method can avoid rigid-body motion damping. In addition, the elastic force vector, the inertia force vector, and the internal damping force vector are derived with the same shape functions to ensure the consistency and independence of the element. Therefore, different assumptions can be made to describe the local deformation of the element. In this paper, the interdependent interpolation element (IIE) and the Kelvin–Voigt model are introduced in the local frame to consider the shear deformation, rotary inertia, and viscoelasticity. Moreover, the presented method is capable of considering the arbitrary curved initial geometry of a beam. Numerical examples show that internal damping dampens only the pure elastic deformation of the beam but does not dampen the rigid-body motion. Three dynamic problems of a beam with a moving boundary or subjected to a moving load are investigated numerically by the presented formulation and the commercial software ansys to verify the validity, versatility, and computational efficiency of the presented formulation.

A General Inheritance Algorithm for Calculating of Arbitrary Moving Samples During Microwave Heating

Moving models, such as translation, rotation, and other motion modes, are widely applied to improve the microwave heating uniformity. However, due to a variety of motion modes, the deformation of mesh, including discontinuity, crossing, and winding, usually occurs in the process of microwave heating calculation. It is a great challenge to numerical simulation of moving samples because of the lack of a common calculation method. In this article, a novel inheritance algorithm, which inherits both the grid and temperature distribution of the sample, can be used to calculate arbitrary moving models of microwave heating process. It is adopted to inherit the grid and temperature distribution in the finite element method to ensure that each temperature calculation result can perfectly correspond to the temperature value of these mesh nodes. By building a 3-D mathematical model of translation, swing, and rotation, the coupling process of electromagnetic field and thermal phenomena in microwave heating was performed and the proposed method was clearly illustrated. Finally, the calculated results are consistent with the experimental results, confirming the accuracy of the algorithm. Compared with the conventional algorithm, the proposed algorithm has a higher precision and practically and can be used to simulate microwave heating of arbitrary motions.

On development of in-core fuel system for PWR reactors: Part I generation of macroscopic cross sections using SCALE 6.0 for use in nodal calculation

This work presents the description of the first part of a methodology applied to perform In-Core Fuel Management (ICFM) in Pressurized Water Reactor (PWR). The ICFM of a PWR reactor consists on defining the best charging or recharging pattern of fuel assemblies inside a reactor for an operational cycle. This means, finding a suitable arrangement of fuel assemblies that optimizes the performance of the reactor, which complies with all safety criteria. Genetic algorithms (GAs) are used to select the arrangements that interact with the reactor physics simulation code, holding the neutron characteristics of each fuel assembly. Therefore, a reliable and fast code was developed accordingly. The consolidated technique of coarse mesh node code that numerically solves the multigroup diffusion equation for two groups of energy, fast and thermal neutrons, in two dimensions was selected. In this type of code, it is essential that each fuel assembly is homogenized and characterized by its macroscopic cross sections, for each reactor’s burnup condition. The cross sections are generated with the support of SCALE 6.0, computational platform developed by the Reactor and Nuclear Systems Division (RNSD), from the Oak Ridge National Laboratory (ORNL). The completeness of the qualification and validation of the results obtained from the homogenization of the fuel assembly by the SCALE was performed comparing the results with actual data of a benchmark reactor. The fully documented Almaraz Nuclear Power Plant provided by the International Atomic Energy Agency (IAEA)-TECDOC-815, has been used as benchmark with successful results.

On the Lagrangian-Eulerian coupling in the immersed finite element/difference method

The immersed boundary (IB) method is a non-body conforming approach to fluid-structure interaction (FSI) that uses an Eulerian description of the momentum, viscosity, and incompressibility of a coupled fluid-structure system and a Lagrangian description of the deformations, stresses, and resultant forces of the immersed structure. Integral transforms with Dirac delta function kernels couple the Eulerian and Lagrangian variables, and in practice, discretizations of these integral transforms use regularized delta function kernels. Many different kernel functions have been proposed, but prior numerical work investigating the impact of the choice of kernel function on the accuracy of the methodology has often been limited to simplified test cases or Stokes flow conditions that may not reflect the method's performance in applications, particularly at intermediate-to-high Reynolds numbers, or under different loading conditions. This work systematically studies the effect of the choice of regularized delta function in several fluid-structure interaction benchmark tests using the immersed finite element/difference (IFED) method, which is an extension of the IB method that uses a finite element structural discretization combined with a Cartesian grid finite difference method for the incompressible Navier-Stokes equations. Whereas the conventional IB method spreads forces from the nodes of the structural mesh and interpolates velocities to those nodes, the IFED formulation evaluates the regularized delta function on a collection of interaction points that can be chosen to be denser than the nodes of the Lagrangian mesh. This opens the possibility of using structural discretizations with wide node spacings that would produce gaps in the Eulerian force in nodally coupled schemes (e.g., if the node spacing is comparable to or broader than the support of the regularized delta function). Earlier work with this methodology suggested that such coarse structural meshes can yield improved accuracy for shear-dominated cases and, further, found that accuracy improves when the structural mesh spacing is increased. However, these results were limited to simple test cases that did not include substantial pressure loading on the structure. This study investigates the effect of varying the relative mesh widths of the Lagrangian and Eulerian discretizations in a broader range of tests. Our results indicate that kernels satisfying a commonly imposed even–odd condition require higher resolution to achieve similar accuracy as kernels that do not satisfy this condition. We also find that narrower kernels are more robust, in the sense that they yield results that are less sensitive to relative changes in the Eulerian and Lagrangian mesh spacings, and that structural meshes that are substantially coarser than the Cartesian grid can yield high accuracy for shear-dominated cases but not for cases with large normal forces. We verify our results in a large-scale FSI model of a bovine pericardial bioprosthetic heart valve in a pulse duplicator.

The convergence properties of a type II complete deficient quartic spline

A novel deficient complete quartic spline S having type II complete endpoint conditions S′′a=f′′a,S′′b=f′′b is constructed, with the expression given in the terms of the second derivative on the mesh nodes, and taking prescribed values on these grid nodes and at midpoints. The existence and uniqueness of this spline is proved, and the error estimates are provided. For less smooth interpolated functions, the interpolation error estimate is given in terms of the uniform modulus of continuity considering S′′a=S′′b=0 as endpoint conditions. Two numerical examples illustrate the geometric properties of this deficient quartic spline interpolation operator. The error estimates are obtained for S,S′,S′′, and S′′′ showing an optimal order of convergence O(h5).

Terraced and 3D Pyramid-Shaped Polymer Single Crystal via Low Temperature-Assisted Microfluidic Technology.

3D pyramidal polymer single crystals provide spatial gradient variations within the crystal molecules, and these variations facilitate the study of the relationship between structure and properties within the molecules of various complexes with anisotropic structures. As described herein, a low-temperature-assisted microfluidic pore channeling approach is proposed to prepare structurally ordered polymer single crystals. A mixture of dichloromethane and dimethyl sulfoxide is used as a prepolymer, and a liquid microfluidic technique is employed to grow the end-functionalized polymers into 3D polymer single crystals. Through the ordered growth of single crystals, a personalized pyramidal pattern with a homogeneous structure is formed. To evaluate the mesh node density, low-temperature growth time and substrate type are also investigated. Rectangular, pyramidal, and dendritic patterns are synthesized via low-temperature single crystal growth. This work shows that low temperature-assisted microfluidics provides a novel means to tune the 3D structure of polymer single crystals.

Data Mesh: Concepts and Principles of a Paradigm Shift in Data Architectures

Inherent to the growing use of the most varied forms of software (e.g., social applications), there is the creation and storage of data that, due to its characteristics (volume, variety, and velocity), make the concept of Big Data emerge. Big Data Warehouses and Data Lakes are concepts already well established and implemented by several organizations, to serve their decision-making needs. After analyzing the various problems demonstrated by those monolithic architectures, it is possible to conclude about the need for a paradigm shift that will make organizations truly data-oriented. In this new paradigm, data is seen as the main concern of the organization, and the pipelining tools and the Data Lake itself are seen as a secondary concern. Thus, the Data Mesh consists in the implementation of an architecture where data is intentionally distributed among several Mesh nodes, in such a way that there is no chaos or data silos, since there are centralized governance strategies and the guarantee that the core principles are shared throughout the Mesh nodes. This paper presents the motivation for the appearance of the Data Mesh paradigm, its features, and approaches for its implementation.