Mesh Algorithm Research Articles

The positivity‐preserving finite volume scheme with fixed stencils for anisotropic diffusion problems on general polyhedral meshes

AbstractTwo kinds of nonlinear cell‐centered positivity‐preserving finite volume schemes are proposed for the anisotropic diffusion problems on general three‐dimensional polyhedral meshes. First, the one‐sided flux on the cell‐faces is discretized using the fixed stencil of all vertices, then the cell‐centered discretization scheme is obtained using the nonlinear two‐point flux approximation. On this basis, a new explicit weighted second‐order vertex interpolation algorithm for arbitrary polyhedral meshes is designed to eliminate the vertex auxiliary unknowns in the scheme. In addition, an improved Anderson acceleration algorithm is adopted for nonlinear iteration. Finally, some benchmark examples are given to verify the convergence and positivity‐preserving property of the two schemes.

3D Reconstruction and Rendering Models in Urban Architectural Design Using Kalman Filter Correction Algorithm

In a virtual 3D city scene, a 3D building model is a must-have element. A 3D reconstruction and rendering algorithm is described in this paper. Model geometry and texture data are simplified separately using LOD model technology. Half-folded mesh algorithm is used to simplify geometric data, while wavelet algorithm is used to compress texture data. Both methods reduce the amount of data that must be stored as well as the amount of data that must be transmitted over the network. To improve the response time of the original algorithm, a Kalman filter correction algorithm is used to optimize the 3D reconstruction beam adjustment algorithm. In this paper, the experimental scheme is used to assess the method. Experiments show that the algorithm reduces the number of primitives drawn by the system while preserving the important geometric features of the scene’s building model. It can also effectively reduce the workload of drawing 3D scenes, improve computer productivity, and reduce computer hardware requirements. This technique is well suited to rendering large-scale 3D urban scenes.

An Open-Source Processing Pipeline for Quad-Dominant Mesh Generation for Class-Compliant Ship Structural Analysis

We present an algorithm for the fully automatic generation of a class-compliant mesh for ship structural analysis. Our algorithm is implemented as an end-to-end solution. It starts from a description of a geometry and produces a class conforming surface mesh as a result. The algorithm consists of two parts, the automatic geometry refinement and the preconditioned Delaunay frontal quad dominant mesh generator. A geometry is described by a dictionary of elements and it contains points, rods, plates, and openings. A dictionary can contain modeling errors such as unintended overlaps or an unintended loss of connectivity between elements. The main contribution of the paper is the automatic geometry refinement algorithm and the virtual stiffener procedure designed to control the local mesh orientation of a marching front meshing algorithm. The geometry refinement algorithm guarantees that the output dictionary will be such that intersections of the boundary edges of plates are guaranteed to be nodes of any mesh generated by tessellating such geometry. The algorithm is implemented in Python, using the open-source Gmsh system together with the Open CASCADE kernel which is used to implement the automatic geometry refinement. We present several benchmark models from an engineering practice to illustrate our claims as well as to benchmark the efficiency of the various stages of the processing pipeline.

Deploying Machine Learning Techniques for Human Emotion Detection.

Emotion recognition is one of the trending research fields. It is involved in several applications. Its most interesting applications include robotic vision and interactive robotic communication. Human emotions can be detected using both speech and visual modalities. Facial expressions can be considered as ideal means for detecting the persons' emotions. This paper presents a real-time approach for implementing emotion detection and deploying it in the robotic vision applications. The proposed approach consists of four phases: preprocessing, key point generation, key point selection and angular encoding, and classification. The main idea is to generate key points using MediaPipe face mesh algorithm, which is based on real-time deep learning. In addition, the generated key points are encoded using a sequence of carefully designed mesh generator and angular encoding modules. Furthermore, feature decomposition is performed using Principal Component Analysis (PCA). This phase is deployed to enhance the accuracy of emotion detection. Finally, the decomposed features are enrolled into a Machine Learning (ML) technique that depends on a Support Vector Machine (SVM), k-Nearest Neighbor (KNN), Naïve Bayes (NB), Logistic Regression (LR), or Random Forest (RF) classifier. Moreover, we deploy a Multilayer Perceptron (MLP) as an efficient deep neural network technique. The presented techniques are evaluated on different datasets with different evaluation metrics. The simulation results reveal that they achieve a superior performance with a human emotion detection accuracy of 97%, which ensures superiority among the efforts in this field.

The sealing mechanism of radial lip seals: A numerical study of the tangential distortion of the sealing edge

The sealing behaviour of elastomeric radial lip seals is essentially affected by the sealing mechanism in the contact area between the sealing edge and the shaft surface. The relative motion between radial lip seal and shaft deforms the sealing edge tangentially in the circumferential direction. This mechanical deformation is considered essential for the sealing mechanism. In this study, a numerical approach is employed to simulate this deformation. A three-dimensional multiscale model serves this purpose. The radial lip seal geometry is described on the macro-scale. On the micro-scale, an artificial rough surface with a stochastic roughness distribution is applied to an ideal sealing edge surface. A new meshing algorithm is used to discretise different sealing edge surfaces and automatically generates structured hexahedral meshes of the sealing edges. Mesh transitions connect the resulting finely meshed sealing edge to the coarsely meshed global macro-scale mesh of the radial lip seal. The paper introduces the modelling method used to simulate the deformation of radial lip seals. Results are presented and discussed with reference to the sealing behaviour. This contributes to a better understanding of the sealing mechanism of radial lip seals. Keywords: radial lip seal, finite element analysis, surface roughness, elastic deformation, elastomers.

Development of a Simulated Portable Mesh Network via ESP8266-Based Devices with Utility Application

Mesh network is very effective for node-to-node communications. In networks that require and demand devices for home monitoring and control, uncommon topology like Mesh is viewed to have a more effective advantage. However, when it comes to networks, Mesh Network is almost left untouched in most studies simply due to the existing network solutions such as WLAN or Bluetooth. The existence of low-powered WPAN devices fill the demand in integrating devices into mesh networks. However, constant configuration could be very complex and difficult for a mesh using existing WPAN devices since nodes constantly move in and out dynamically in the mesh network. This study focused on the development of a simulated mesh network through ESP8266 enabled devices to deliver a straightforward setup and portable connectivity. The study also developed a utility application that integrates an algorithm for node network operations, and a facility that keeps track of mesh network information including delays, node connections, and data transmission. Three(3) portable ESP8266 devices were used and configured in the study. The devices were integrated in a simulated mesh network and subjected to network processes including identity tagging, dynamic connection, routing, One-way Delay and Payload Size Tests. Results of One-Way Delay and Payload Size Tests indicate consistency of transmission and receiving of data of nodes connecting and disconnecting to the simulated network. This can be used as basis in extending further into more high-end nodes like handheld devices and even computers. Similarly, the utilization of dedicated algorithm for Mesh in this study proved that portability can be achieved to avoid loss of connection when nodes abruptly fail in the network.

Reinforcement Learning Based Fault-Tolerant Routing Algorithm for Mesh Based NoC and Its FPGA Implementation

Network-on-Chip (NoC) has emerged as the most promising on-chip interconnection framework in Multi-Processor System-on-Chips (MPSoCs) due to its efficiency and scalability. In the deep sub-micron level, NoCs are vulnerable to faults, which leads to the failure of network components such as links and routers. Failures in NoC components diminish system efficiency and reliability. This paper proposes a Reinforcement Learning based Fault-Tolerant Routing (RL-FTR) algorithm to tackle the routing issues caused by link and router faults in the mesh-based NoC architecture. The efficiency of the proposed RL-FTR algorithm is examined using System-C based cycle-accurate NoC simulator. Simulations are carried out by increasing the number of links and router faults in various sizes of mesh. Followed by simulations, real-time functioning of the proposed RL-FTR algorithm is observed using the FPGA implementation. Results of the simulation and hardware shows that the proposed RL-FTR algorithm provides an optimal routing path from the source router to the destination router.

A Study on the Whole-skin Peeling System of a Snakehead Based on Three-dimensional Reconstruction

HighlightsA 3D reconstruction algorithm is proposed to determine the snakehead area.The whole-skin peeling system of snakehead is designed by a convolutional neural network.An automatic whole-skin peeling device is presented with computer vision technology.Abstract. A whole-skin peeling system for a snakehead is designed in this article. The snakehead photos are taken from multiple angles and are first filtered to extract the image features, before reconstructing the sparse model. Then, the characteristic parameters of the snakehead are determined through the point cloud coordinates, and dense reconstruction is carried out based on sparse points. The accurate three-dimensional spatial coordinates of the snakehead are obtained by the octree algorithm and Poisson surface reconstruction algorithm. Based on the triangular meshing algorithm, the skin area of a snakehead is calculated to determine whether the snakehead meets the peeling conditions. A trained Faster Region Convolutional Neural Network (R-CNN) is used to identify the fin position on the snakehead reconstruction model and program the cutting route on the fish neck, while the cutting route of the fish belly is determined by selecting the area of the excretory hole through the ROI region of interest. Finally, the designed mechanical structure is used to peel the whole skin of the snakehead. The experimental results show that the maximum fluctuation rate of the snakehead area calculated by the proposed three-dimensional reconstruction algorithm is less than 4.0%, and the accuracy reaches 87.3%. The average precision (AP) for the determination method of the fish neck cutting position on the snakehead is 90.89%, which proves the effectiveness and feasibility of this method. The present results provide useful technical support for automating fish whole-skin peeling and shedding light on the accurate determination of the surface area and the extrication of the morphological feature parameters of other organisms. Keywords: Neural network, Point cloud, Snakehead, Skin peeling, Three-dimensional reconstruction.

Aerosol transmission risk of COVID-19 when passengers move slowly in a line at the airport terminal

The airport terminal with high numbers of occupied passengers has potentially become high risk region for aerosol transmission of COVID-19. In this paper, the Eulerian-Lagrangian approach and realizable k–ε turbulence model is used to numerically simulate the airflow organization and aerosol transmission when passengers move slowly in a line. During the aerosol transmission period, evaporation is also enrolled as it is a key factor influencing particle size distribution at the beginning of aerosol transmission from the human. In addition, the process of passenger moving in the airport terminal is realized by employing dynamic mesh algorithms. The results of the study show that people who are behind the infected person during the queuing movement have a higher risk of infection than those who are in front. In addition, the disturbance of people walking has an important influence on the distribution of aerosols.

Functional norms, condition numbers and numerical algorithms in algebraic geometry

Abstract In numerical linear algebra, a well-established practice is to choose a norm that exploits the structure of the problem at hand to optimise accuracy or computational complexity. In numerical polynomial algebra, a single norm (attributed to Weyl) dominates the literature. This article initiates the use of $L_p$ norms for numerical algebraic geometry, with an emphasis on $L_{\infty }$ . This classical idea yields strong improvements in the analysis of the number of steps performed by numerous iterative algorithms. In particular, we exhibit three algorithms where, despite the complexity of computing $L_{\infty }$ -norm, the use of $L_p$ -norms substantially reduces computational complexity: a subdivision-based algorithm in real algebraic geometry for computing the homology of semialgebraic sets, a well-known meshing algorithm in computational geometry and the computation of zeros of systems of complex quadratic polynomials (a particular case of Smale’s 17th problem).

A tracking strategy for multi‐branched crack tips in phase‐field modeling of dynamic fractures

AbstractThe well‐received phase‐field method smears the discrete cracks in the damaged bands, blurring the explicit crack tip. However, identifying the location of the crack tip is sometimes vital. The widely used scheme at present considers the forefront of a phase‐field contour as the crack tip. Such a method, to our best knowledge, is inapplicable for branched cracks, which motivates us to develop a novel stepwise identification strategy for multi‐branched crack tips termed si‐MCT. Instead of searching for crack tips globally, the proposed si‐MCT realizes this in the chosen deliberately local regions (searching regions), and then automatically updates these regions as the cracks propagate. For the robust implementation of si‐MCT, a novel concept of active crack tip zone is also proposed to cope with the extreme circumstances where adjacent crack paths are too close to interfere with identifying the crack tip. Furthermore, the core algorithms and specific procedures of the proposed strategy are also elaborated. Moreover, several representative tests are studied, showing the bright prospect of si‐MCT in dynamic multi‐branch crack tracking and adaptive mesh algorithm.

An immersed boundary-lattice Boltzmann framework for fully resolved simulations of non-spherical particle settling in unbounded domain

Particle settling at moderate to high Reynolds number takes a considerable distance to reach a periodical or statistically steady regime. Hence, hardware memory limitations in fully resolved simulations constrain the maximum domain size for this flow class. Due to the locality in most of its algorithms, the Lattice Boltzmann Method (LBM) is increasingly popular for CFD studies. In the present paper, a domain transferring scheme is implemented in LBM, enabling simulations of particle motion in a virtually infinite domain, and it is combined with a high-quality Lagrangian mesh algorithm to be solved with the Immersed Boundary Method (IBM). A thorough mesh generation procedure for ellipsoidal particles is disclosed, as well as an extension of the internal mass compensation strategy of Suzuki and Inamuro (2011). Comparison with analytical results shows that the numerical model appropriately describes the particle rotation and can predict a terminal velocity close to Stokes solution. The numerical results of a buoyant sphere moving diagonally presented remarkable concordance with experimental data. Also, an excellent agreement with a numerical study of oblate spheroids settling in a vast domain was found. The domain transferring scheme reduced the memory demand in one order of magnitude.

A Feasibility Study of LiDAR-Enhanced Augmented Reality on a Handheld Device for Collision Detection and Patient Positioning

<h3>Purpose/Objective(s)</h3> This study investigates the feasibility of using a commercially available handheld device with augmented reality (AR) cameras, enhanced by light detection and ranging (LiDAR), for pre-treatment collision detection and patient positioning. The on-device LiDAR scanner detects object depths with direct time-of-flight (ToF) measurements, thus improving the accuracy of contrast-based visual depth estimation. Our proposed approach leverages AR for near-real-time reconstruction of patient external contour during simulation and setup. This is advantageous compared with conventional laser-tattoo alignment and photo-based patient position, by providing an intuitive 3D rendering of the patient's body and immobilization devices at arbitrary angles. <h3>Materials/Methods</h3> Two possible modes for AR-assisted positioning were investigated: mesh and point-cloud mode. In mesh mode, surface mesh of a mock pediatric phantom (50 × 40 × 15 cm³) was rapidly reconstructed via the default meshing algorithm from the software development kit (SDK). Resulting 3D contours were manually registered to a computerized tomography (CT) scan of the phantom in a third-party open source image processing suite. For point cloud mode, surface anchor points of the phantom and its supporting devices were detected and placed in the real-world frame of reference, which were subsequently overlaid on the real-time color image. Each handheld scanning session was kept at 30 seconds. The native pulse intervals of 0.2 – 0.5 nsec of the LiDAR scanner were used; depth map was updated at 60 frames per second (fps). Scanning method was kept consistent and mimicked CT scans, with the device camera rotated about the superior-inferior axis pointing towards the phantom. The resolution of the resulting surface mesh and point cloud was quantified. Extent of the volume reconstructed was estimated. <h3>Results</h3> The scan and on-device real-time reconstruction were completed within 30 seconds. We successfully extracted the reconstructed mesh and registered that to a CT scan of the phantom. A mean distance of 1.5 ± 1.0 cm between each adjacent vertex was achieved. The point cloud density was on an average 20.9 ± 0.9 points/cm², with decreased point density 35cm superior to the phantom midpoint (10.0 points/cm²). Both modes captured approximately 4 × 4 × 4m³ volume of the phantom and its supporting structures. <h3>Conclusion</h3> AR has emerged as a promising modality for surface guided patient positioning, yet several previous studies have found a lack of sufficient mesh resolution and/or accuracy. LiDAR improves both aspects with directly measured depth information. We demonstrated that sub-cm full 3D rendering of the patient body contour and supporting device is achievable with a handheld device in under 30 seconds, which could provide a viable option for improved guidance on collision check and patient positioning.

Computational tibial bone remodeling over a population after total knee arthroplasty: A comparative study.

Periprosthetic bone loss is an important factor in tibial implant failure mechanisms in total knee arthroplasty (TKA). The purpose of this study was to validate computational postoperative bone response using longitudinal clinical DEXA densities. Computational remodeling outcome over a population was obtained by incorporating the strain‐adaptive remodeling theory in finite element (FE) simulations of 26 different tibiae. Physiological loading conditions were applied, and bone mineral density (BMD) in three different regions of interest (ROIs) was considered over a postoperative time of 15 years. BMD outcome was compared directly to previously reported clinical BMD data of a comparable TKA cohort. Similar trends between computational and clinical bone remodeling over time were observed in the two proximal ROIs, with most rapid bone loss taking place in the initial months after TKA and BMD starting to level in the following years. The extent of absolute proximal BMD change was underestimated in the FE population compared with the clinical subject group, which might be the result of significantly higher initial clinical baseline BMD values. Large differences in remodeling response were found in the distal ROI, in which resorption was measured clinically, but a large BMD increase was predicted by the FE models. Multiple computational limitations, related to the FE mesh, loading conditions, and strain‐adaptive algorithm, likely contributed to the extensive local bone formation. Further research incorporating subject‐specific comparisons using follow‐up CT scans and more extensive physiological knee loading is recommended to optimize bone remodeling more distal to the tibial baseplate.

SPEARS: A Database-Invariant Spectral modeling API

The Spectral Physics Environment for Advanced Remote Sensing (SPEARS) application programming interface (API) is a Python-based, line-by-line, local thermal equilibrium (LTE) spectral modeling code which is optimized for simultaneously synthesizing optical spectra from any combination of fundamental spectroscopic databases. In this article, we contribute two novel spectral modeling techniques to the scientific literature. First we describe how SPEARS integrates a physics-based collisional model for calculating pressure broadening in the absence of available broadening coefficients. With this collisional model implementation, a generalized approach to fundamental spectroscopic databases can be achieved across multiple databases. We also detail our adaptive grid mesh algorithm developed to make the code scalable for simulating large spectral bandwidths at high spectral fidelity using intuitive grid parameters. We present comparisons to other modeling tools, experiments, and provide a discussion on the SPEARS user interface.

Open-Source Script for Design and 3D Printing of Porous Structures for Soil Science

Three-dimensional (3D) printing in soil science is relatively rare but offers promising directions for research. Having 3D-printed soil samples will help academics and researchers conduct experiments in a reproducible and participatory research network and gain a better understanding of the studied soil parameters. One of the most important challenges in utilizing 3D printing techniques for soil modeling is the manufacturing of a soil structure. Until now, the most widespread method for printing porous soil structures is based on scanning a real sample via X-ray tomography. The aim of this paper is to design a porous soil structure based on mathematical models rather than on samples themselves. This can allow soil scientists to design and parameterize their samples according to their desired experiments. An open-source toolchain is developed using a Lua script, in the IceSL slicer, with graphical user interface to enable researchers to create and configure their digital soil models, called monoliths, without using meshing algorithms or STL files which reduce the resolution of the model. Examples of monoliths are 3D-printed in polylactic acid using fused filament fabrication technology with a layer thickness of 0.20, 0.12, and 0.08 mm. The images generated from the digital model slicing are analyzed using open-source ImageJ software to obtain information about internal geometrical shape, porosity, tortuosity, grain size distribution, and hydraulic conductivities. The results show that the developed script enables designing reproducible numerical models that imitate soil structures with defined pore and grain sizes in a range between coarse sand (from 1 mm diameter) to fine gravel (up to 12 mm diameter).

Applications of mesh algorithms and self-dual mesh geometries of root Coxeter orbits to a Horn-Sergeichuk type problem

One of the main aims of the paper is to develop the mesh geometry technique for corank-two edge-bipartite graphs Δ with n+2≥3 vertices, and the mesh algorithms introduced in [30,33] and successfully studied in our recent article [42]. We introduce and study the concept of a self-duality of mesh geometries Γ(RˆΔ,ΦΔ) viewed as ΦΔ-mesh translation quivers. We show how self-dualities of mesh geometries Γ(RˆΔ,ΦΔ) and the mesh geometry technique is applied to an affirmative algorithmic solution of so called Horn-Sergeichuk type problem [9, Problem 4.3] on the self-congruency of square integer matrices A∈Mn+2(Z), for the class of non-symmetric Gram matrices A=GˇΔ of corank-two loop-free edge-bipartite graphs Δ, with n+2≤6 vertices. More precisely, we show that each of the mesh geometries Γ(RˆΔ,ΦΔ) is self-dual, we construct its dual form Γ(RˆΔ,ΦΔ)op=Γ(RˆΔ,ΦΔ−1) isomorphic with Γ(RˆΔ,ΦΔ), and we construct a canonical self-duality isomorphism fΔ:Γ(RˆΔ,ΦΔ)→Γ(RˆΔ,ΦΔ)op of mesh translation quivers. Using the self-duality fΔ we construct combinatorial algorithms such that, given a square Gram matrix A=GˇΔ∈Mn+2(Z) of Δ lying in this class, they are able to compute a Z-invertible matrix B∈Mn+2(Z) that coincide with its inverse B−1 and defines the congruence of A with Atr, i.e., the equation Atr=Btr⋅A⋅B is satisfied.An idea of our solution is outlined in Section 8 of our recent article [42], where among others two of our 13 algorithms solving the problem are constructed. The remaining 11 algorithms are constructed in the present article. We do it by means of the structure of the standard self-dual ΦΔ-mesh translation quiver Γ(RˆΔ,ΦΔ) (called a geometry) canonically associated with Δ, consisting of ΦΔ-meshes of ΦΔ-orbits OΔ(w) of vectors w∈RˆΔ⊆Zn+2, where ΦΔ:Zn+2→Zn+2 is the Coxeter transformation of Δ. We construct in the paper such self-dual ΦΔ-mesh geometry Γ(RˆΔ,ΦΔ), for each of the corank-two loop-free edge-bipartite graphs Δ, with n+2≤6 vertices.

Fast k-Nearest Neighbor on a Navigation Mesh

We consider the k-Nearest Neighbour problem in a two-dimensional Euclidean plane with obstacles (OkNN). Existing and state of the art algorithms for OkNN are based on incremental visibility graphs and as such suffer from a well known disadvantage: costly and online visibility checking with quadratic worst-case running times. In this work we develop a new OkNN algorithm which avoids these disadvantages by representing the traversable space as a collection of convex polygons; i.e. a Navigation Mesh. We then adapt an recent and optimal navigation mesh algorithm, Polyanya, from the single-source single-target setting to the the multi-target case. We also give two new heuristics for OkNN. In a range of empirical comparisons we show that our approach can be orders of magnitude faster than competing methods that rely on visibility graphs.

Automatic triangulated mesh generation of pulmonary airways from segmented lung 3DCTs for computational fluid dynamics.

Computational fluid dynamics (CFD) of lung airflow during normal and pathophysiological breathing provides insight into regional pulmonary ventilation. By integrating CFD methods with 4D lung imaging workflows, regions of normal pulmonary function can be spared during treatment planning. To facilitate the use of CFD simulations in a clinical setup, a robust, automated, and CFD-compliant airway mesh generation technique is necessary. We define a CFD-compliant airway mesh to be devoid of blockages of airflow and leaks in the airway path, both of which are caused by airway meshing errors that occur when using conventional meshing techniques. We present an algorithm to create a CFD-compliant airway mesh in an automated manner. Beginning with a medial skeleton of the airway segmentation, the branches were tracked, and 3D points at which bifurcations occur were identified. Airway branches and bifurcation features were isolated to allow for automated and careful meshing that considered their anatomical nature. We present the meshing results from three state-of-the-art tools and compare them with the meshes generated by our algorithm. The results show that fully CFD-compliant meshes were automatically generated for an ideal geometry and patient-specific CT scans. Using an open-source smoothed-particle hydrodynamics CFD implementation, we compared the airflow using our approach and conventionally generated airway meshes. Our meshing algorithm was able to successfully generate a CFD-compliant mesh from pre-segmented lung CT scans, providing an automatic meshing approach that enables interventional CFD simulations to guide lung procedures such as radiotherapy or lung volume reduction surgery.

Cylinder-lamina system fluid–structure interaction problem solved with an original OpenFOAM code

In numerical simulations, the partitioned approach allows treating a multi-physics phenomenon as two different computational fields, which are solved separately with their respective mesh discretisation and algorithms. This is of particular interest to fluid–structure interaction (FSI) problems for their complex resolution. In this respect, through the partitioned approach, ModsFsiFoam (MODalSuperpositionFsiFoam) solver has been developed. It allows the application of two different methods for fluid and solid solutions. In particular, it is based on a theoretical approach, the modal superposition principle, for the structural solution; this method provides a certain result for the linear structural field. The FVM (Finite VolumeMethod), by far the most widely used method for fluid-dynamics and gas-dynamics problems, has been used instead to solve the Navier–Stokes equations for an incompressible laminar flow of Newtonian fluid. The interfacial conditions have been used to pass information between the domains through a coupling algorithm. Implemented in OpenFOAM, a development environment consisting of libraries and applications for Linux distributions, written in the C++ source code, ModsFsiFoam solver has been already applied with satisfactory results to a typical fluid–structure interaction case found in literature, i.e. a system composed by an inverted flag treated as a flexible lamina, clamped to a wind tunnel wall, in which airflow is introduced in the axial direction. In this work, ModsFsiFoam solver outputs are compared with a system, the results of which are known for both fluid-dynamics and structural fields. The configuration consists of a laminar incompressible channel flow around a solid structure with an elastic part.