Mesh-based Method Research Articles

Guidance for Clinical Evaluation under the Medical Device Regulation through Automated Scoping Searches

The Medical Device Regulation (MDR) in Europe aims to improve patient safety by increasing requirements, particularly for the clinical evaluation of medical devices. Before the clinical evaluation is initiated, a first literature review of existing clinical knowledge is necessary to decide how to proceed. However, small and medium-sized enterprises (SMEs) lacking the required expertise and funds may disappear from the market. Automating searches for the first literature review is both possible and necessary to accelerate the process and reduce the required resources. As a contribution to the prevention of the disappearance of SMEs and respective medical devices, we developed and tested two automated search methods with two SMEs, leveraging Medical Subject Headings (MeSH) terms and Bidirectional Encoder Representations from Transformers (BERT). Both methods were tailored to the SMEs and evaluated through a newly developed workflow that incorporated feedback resource-efficiently. Via a second evaluation with the established CLEF 2018 eHealth TAR dataset, the more general suitability of the search methods for retrieving relevant data was tested. In the real-world use case setting, the BERT-based method performed better with an average precision of 73.3%, while in the CLEF 2018 eHealth TAR evaluation, the MeSH-based search method performed better with a recall of 86.4%. Results indicate the potential of automated searches to provide device-specific relevant data from multiple databases while screening fewer documents than in manual literature searches.

Sizing of the Motor Geometry for an Electric Aircraft Propulsion Switched Reluctance Machine Using a Reluctance Mesh-Based Magnetic Equivalent Circuit

The switched reluctance motor (SRM) is a promising candidate for electric propulsion systems. In the design process of an SRM, the motor geometry needs to be determined. Using the finite element method (FEM) might be time-consuming for the sizing of the motor geometry. As an alternative, electromagnetic models based on a magnetic equivalent circuit (MEC) can be utilized for the sizing of an SRM. MEC models require fewer computational resources and can help determine the electromagnetic performance with reasonable accuracy. Using the conventional MEC method for SRM sizing might be challenging since the flux pattern inside the motor should be changed for different motor dimensions. In order to address this challenge, this paper applies a reluctance mesh-based MEC technique to determine the geometry of a three-phase 12/16 SRM for a high-lift motor in the NASA Maxwell X-57 electric aircraft. A comprehensive reluctance mesh-based MEC model is developed for this purpose. Both the static and dynamic characteristics of the SRM geometry are evaluated using the reluctance mesh-based MEC method. The determined geometry is verified using the results computed from FEM.

Hydrophobic and Hydrophilic Solid-Fluid Interaction

We propose a novel solid-fluid coupling method to capture the subtle hydrophobic and hydrophilic interactions between liquid, solid, and air at their multi-phase junctions. The key component of our approach is a Lagrangian model that tackles the coupling, evolution, and equilibrium of dynamic contact lines evolving on the interface between surface-tension fluid and deformable objects. This contact-line model captures an ensemble of small-scale geometric and physical processes, including dynamic waterfront tracking, local momentum transfer and force balance, and interfacial tension calculation. On top of this contact-line model, we further developed a mesh-based level set method to evolve the three-phase T-junction on a deformable solid surface. Our dynamic contact-line model, in conjunction with its monolithic coupling system, unifies the simulation of various hydrophobic and hydrophilic solid-fluid-interaction phenomena and enables a broad range of challenging small-scale elastocapillary phenomena that were previously difficult or impractical to solve, such as the elastocapillary origami and self-assembly, dynamic contact angles of drops, capillary adhesion, as well as wetting and splashing on vibrating surfaces.

An Automatic Generalization Method for a Dense Road Network Area Considering Spatial Structural Features as Constraints

Road networks are the skeletal elements of topographic maps at different scales, and road selection is a prerequisite for implementing continuous multiscale spatial representations of road networks. The mesh-based approach is a common, advanced and powerful method for road selection in dense road areas in which small meshes are removed and road segments with the least importance in each mesh are eliminated. However, small meshes in a map can be classified into two types: aggregated small meshes and isolated small meshes. The number of the former is small, and that of the latter is large. Existing methods are generally applicable for the latter, and some or even most spatial characteristics will be lost when they are applied to the former; as a result, the road selection quality will be affected. Therefore, as a supplement to the mesh-based selection method, this paper proposed an automatic generalization method of dense road network areas (areas formed by aggregated small meshes) considering spatial structural features as constraints. First, the aggregated areas of small meshes were identified based on the number of adjoining small meshes, and the boundaries of aggregated areas are extracted and used as hard constraints during mesh elimination. Second, the starting meshes were redefined by simultaneously considering the edge features and mesh density of small meshes, and an ordinal elimination algorithm was proposed to eliminate the meshes in the stroke connection direction. Third, road selection was implemented by identifying the starting meshes and sequentially processing the related mesh pairs. This iterative process continued until all mesh densities of the newly formed meshes are beyond the threshold or the problem becomes a simple elimination problem involving two adjoining small meshes or one isolated small mesh. Finally, a 1:10,000 standard topographic road map for Jiangsu Province, China, was used for validation. The experimental results showed that in the aggregated areas with two small meshes, 31% of the areas obtained the same selection results by using the mesh-based method and the proposed method, and the remaining 69% obtained a more compact result with the proposed method. Moreover, for all aggregated areas with more than two small meshes, the spatial distribution structure of small meshes was preserved better by the proposed method.

Ontology-based categorization of clinical studies by their conditions

ObjectiveThe free-text Condition data field in the ClinicalTrials.gov is not amenable to computational processes for retrieving, aggregating and visualizing clinical studies by condition categories. This paper contributes a method for automated ontology-based categorization of clinical studies by their conditions. Materials and MethodsOur method first maps text entries in ClinicalTrials.gov’s Condition field to standard condition concepts in the OMOP Common Data Model by using SNOMED CT as a reference ontology and using Usagi for concept normalization, followed by hierarchical traversal of the SNOMED ontology for concept expansion, ontology-driven condition categorization, and visualization. We compared the accuracy of this method to that of the MeSH-based method. ResultsWe reviewed the 4,506 studies on Vivli.org categorized by our method. Condition terms of 4,501 (99.89%) studies were successfully mapped to SNOMED CT concepts, and with a minimum concept mapping score threshold, 4,428 (98.27%) studies were categorized into 31 predefined categories. When validating with manual categorization results on a random sample of 300 studies, our method achieved an estimated categorization accuracy of 95.7%, while the MeSH-based method had an accuracy of 85.0%. ConclusionWe showed that categorizing clinical studies using their Condition terms with referencing to SNOMED CT achieved a better accuracy and coverage than using MeSH terms. The proposed ontology-driven condition categorization was useful to create accurate clinical study categorization that enables clinical researchers to aggregate evidence from a large number of clinical studies.

Cost-Driven Design of Printed Wideband Antennas with Reduced Silver Ink Consumption for the Internet of Things.

The Internet of Things (IoT) accelerates the need for compact, lightweight and low-cost antennas combining wideband operation with a high integration potential. Although screen printing is excellently suited for manufacturing conformal antennas on a flexible substrate, its application is typically limited due to the expensive nature of conductive inks. This paper investigates how the production cost of a flexible coplanar waveguide (CPW)-fed planar monopole antenna can be reduced by exploiting a mesh-based method for limiting ink consumption. Prototypes with mesh grids of different line widths and densities were screen-printed on a polyethylene terephthalate (PET) foil using silver-based nanoparticle ink. Smaller line widths decrease antenna gain and efficiency, while denser mesh grids better approximate unmeshed antenna behavior, albeit at the expense of greater ink consumption. A meshed prototype of with almost 80% ink reduction compared to an unmeshed counterpart is presented. It is capable of providing wideband coverage in the IMT/LTE-1/n1 (1.92–2.17 GHz), LTE-40/n40 (2.3–2.4 GHz), 2.45 GHz ISM (2.4–2.4835 GHz), IMT-E/LTE-7/n7 (2.5–2.69 GHz), and n78 5G (3.3–3.8 GHz) frequency bands. It exhibits a peak radiation efficiency above 90% and a metallized surface area of cm2 (yielding an ink-to-total-surface ratio of 12.2%).

Efficient coupled deep neural networks for the time-dependent coupled Stokes-Darcy problems

In this paper, we propose and investigate an efficient method called CDNNs (Coupled Deep Neural Networks) for the time-dependent coupled Stokes-Darcy problems. Specifically, we encode complex interface conditions related to the variables of the coupled problems into several neural networks to constrain the approximation solution. We define a custom loss function to guarantee the physical properties of the numerical solution as well as the conservation of the energy. In particular, the present method is mesh-free since it only inputs random spatiotemporal points and can avoid the difficulties and complexities caused by the mesh-based method. Moreover, our method is parallel, it solves each variable simultaneously and independently. Furthermore, we obtain the convergence analysis to illustrate the capabilities of our method for solving the coupled problems. Numerical experiments further demonstrate the accuracy and efficiency of the proposed method.

Calculation of the number of ship collision candidates using mesh-based estimation method for ship traffic data

Predicting and assessing the ship–ship collision possibility in waters are important for discussions on ship traffic safety. The geometric number of collision candidates is one of the most commonly used indexes for representing the frequency of multi-ship encounters that have potential collisions. It has often been estimated for ship traffic in a delimited area based on existing concepts. However, to discuss ship traffic safety in wide-congested waters where ships navigate along various courses and various ship encounters occur, a comprehensive understanding of potential collisions corresponding to all encounter characteristics, such as the encounter angle and location, is necessary. This paper proposes a method, called a “mesh-based estimation method,” to calculate the geometric number of collision candidates. It can deal with various encounter angles by introducing a computational mesh to comprehensively assess potential collisions in wide-congested waters. The validation of the method is conducted by applying it to simple ship traffic and comparing the calculated result with a result calculated based on a conventional approach. In addition, the method is applied to traffic data of AIS-equipped ships navigating in Tokyo Bay in Japan to show locations that have potential collisions based on the encounter angles.

Automated measurement of dairy cows body size via 3D point cloud data analysis

Body measurement plays an important role in the breeding and production of dairy cows. Body measurement is mainly done manually, which is laborious, imprecise, and prone to stressful behavior in animals. A portable non-contact 3D measurement system of dairy cow body using smartphones was proposed in this study. Reconstruction of 3D point clouds scene containing the cow through a Structure-from-Motion (SfM) photogrammetry, the RANdom SAmple Consensus (RANSAC), and the Euclidean clustering were used to segment the scene and extract cow’s point clouds. Aiming to solve the holes in the cow point cloud caused by the barrier and legs occlusion, a completion method based on the spline curve with a smoothing factor was proposed. The automatic measurement of body size was realized through morphological features. The accuracy of the proposed system was evaluated in a commercial dairy farm. Compared with mesh-based method, the proposed point cloud hole completion method reduced the maximum relative errors of chest girth and chest width by 2.22% and 2.18%. Under different cow postures, the average relative error between automatic body size measurement algorithm and manual calibration was less than 4.67%. The average relative error between the measured value of the non-contact measurement system and the actual value of withers height, body length, chest girth, and chest width were 2.41%, 3.18%, 4.37%, and 6.12%, respectively. The results showed that the proposed method can be used as an automatic and non-contact approach for measuring animal body size.

Physics-informed neural networks for solving the Boltzmann equation of the electron velocity distribution function in weakly ionized plasmas

The equilibrium electron velocity distribution function (EVDF) and electron transport coefficient in weakly ionized plasmas under crossed DC uniform electric and magnetic fields are calculated via the Boltzmann equation (BE) using physics-informed neural networks (PINNs). The latent solution of the BE is represented by an artificial neural network, and then the neural network is trained to respect the BE. By leveraging automatic differentiation, no mesh generation in velocity space is required, allowing us to calculate the three-dimensional EVDF properly with 0.01% of memory capacity required for the conventional mesh-based method. The EVDF and electron transport coefficients in SF6 calculated from the PINNs are benchmarked by comparing with those calculated from the Monte Carlo simulation (MCS). In most cases, the relative difference between the electron transport coefficient calculated from the PINNs and MCS is found to be within 1%.

Reluctance Mesh-Based Magnetic Equivalent Circuit Modeling of Switched Reluctance Motors for Static and Dynamic Analysis

Designing a switched reluctance machine (SRM) is an iterative process. Sizing of the motor is one of the fundamental steps where the main geometry parameters are determined to achieve the performance requirements. Usually, finite element method (FEM) is employed in all design stages, which might require extensive computational burden. The magnetic equivalent circuit (MEC) method is an alternative for typical FEM. There are two approaches for the MEC method: conventional MEC method and reluctance mesh-based MEC method. The conventional MEC method can be challenging when modifying the motor geometry while conducting dynamic analysis with current control. This article presents a reluctance mesh-based MEC model for SRMs that can overcome those challenges. Reluctance mesh-based MEC models are developed for three-phase 6/4, 6/16, 12/8 SRMs and four-phase 8/6, 8/10, and 16/12 SRMs. The models calculate the static and dynamic characteristics of the considered SRMs. The static and dynamic characteristics are compared with the results obtained from FEM and experimental tests.

Generalized finite difference method (GFDM) based analysis for subsurface flow problems in anisotropic formation

This paper applies the meshless generalized finite difference method (GFDM) to analyze the subsurface flow problem in anisotropic formations for the first time, and develops the treatment methods of anisotropic permeability tensor in continuous function and discrete distribution expressions respectively. In particular, in case of the common discrete distribution expression of anisotropic permeability tensor in reservoir simulation, this paper suggests combining general difference operators and harmonic average scheme to simply and efficiently obtain the meshless discrete scheme of the anisotropic flow equation. Three numerical examples of steady and transient flow in the rectangular computational domain, transient flow with complex boundary, and steady flow with strongly discontinuous anisotropic permeability are used to verify the high accuracy and good convergence of GFDM to handle anisotropic flow problems. Compared with the traditional mesh-based reservoir numerical simulation method that replies on laborious gridding to discretize the reservoir domain and complicated multi-point flux approximation (MPFA) to handle discrete distribution anisotropic permeability tensor, the meshless GFDM can be more practically applied to the anisotropic flow problems in the reservoir domain with complex geometry and complex boundary conditions. Besides, it is found that the radius of the influence domain has little impact on the accuracy of steady flow. For the transient flow, it generally holds that the larger the radius of the influence domain, the lower the calculation accuracy in case of Cartesian collocation. In sum, this work provides an efficient and simple meshless solver to handle anisotropic flow problems in porous media under GFDM framework, which reveals the great application potential of GFDM in reservoir numerical simulation.

Development of the Concurrent Multiscale Discrete-Continuum Model and Its Application in Plasticity Size Effect

A concurrent multiscale model coupling discrete dislocation dynamics to the finite element method is developed to investigate the plastic mechanism of materials at micron/submicron length scales. In this model, the plastic strain is computed in discrete dislocation dynamics (DDD) and transferred to the finite element method (FEM) to participate in the constitutive law calculation, while the FEM solves the complex boundary problem for DDD simulation. The implementation of the whole coupling scheme takes advantage of user subroutines in the software ABAQUS. The data structures used for information transferring are introduced in detail. Moreover, a FE mesh-based regularization method is proposed to localize the discrete plastic strain to continuum material points. Uniaxial compression tests of single crystal micropillars are performed to validate the developed model. The results indicate the apparent dependence of yield stress on sample size, and its underlying mechanisms are also analyzed.

A Hybrid Multiscale Finite Cloud Method and Finite Volume Method in Solving High Gradient Problem

Meshfree methods are always the alternatives to be considered besides the finite element method in dealing with complex engineering problems. Among these complex problems, there are problems where discontinuities or high gradients may only emerge at a small region of a domain and the remaining parts of the domain are smooth and continuous. In this case, adding nodes to the critical region is essential for the better accuracy of solutions. It would be effective if a meshfree method is applied to the critical region and a mesh-based method is employed to solve the remaining part of the domain since node refinement is easier for a meshfree method whereas a mesh-based method is simple to develop and capable of producing accurate solutions for smooth regions. In this study, the finite cloud method (FCM) is coupled with the finite volume method (FVM) such that node refinement only takes place at the region where the FCM is applied. A handshaking approach is proposed to enforce the continuity near the interface where both methods are applied. Numerical examples and computation methods are presented in this paper and the numerical results are examined.

Performance analyses of mesh-based local Finite Element Method and meshless global RBF Collocation Method for solving Poisson and Stokes equations

Steady and unsteady Poisson and Stokes equations are solved using mesh dependent Finite Element Method and meshless Radial Basis Function Collocation Method to compare the performances of these two numerical techniques across several criteria. The accuracy of Radial Basis Function Collocation Method with multiquadrics is enhanced by implementing a shape parameter optimization algorithm. For the time-dependent problems, time discretization is done using Backward Euler Method. The performances are assessed over the accuracy, runtime, condition number, and ease of implementation. Three error kinds considered; least square error, root mean square error and maximum relative error. To calculate the least square error using meshless Radial Basis Function Collocation Method, a novel technique is implemented. Imaginary numerical solution surfaces are created, then the volume between those imaginary surfaces and the analytic solution surfaces is calculated, ensuring a fair error calculation. Lastly, all results are put together and trends are observed. The change in runtime vs. accuracy and number of nodes; and the change in accuracy vs. the number of nodes is analyzed. The study indicates the criteria under which Finite Element Method performs better and conditions when Radial Basis Function Collocation Method outperforms its mesh dependent counterpart.

A Direct-Forcing Immersed Boundary Method for Incompressible Flows Based on Physics-Informed Neural Network

The application of physics-informed neural networks (PINNs) to computational fluid dynamics simulations has recently attracted tremendous attention. In the simulations of PINNs, the collocation points are required to conform to the fluid–solid interface on which no-slip boundary condition is enforced. Here, a novel PINN that incorporates the direct-forcing immersed boundary (IB) method is developed. In the proposed IB-PINN, the boundary conforming requirement in arranging the collocation points is eliminated. Instead, velocity penalties at some marker points are added to the loss function to enforce no-slip condition at the fluid–solid interface. In addition, force penalties at some collocation points are also added to the loss function to ensure compact distribution of the volume force. The effectiveness of IB-PINN in solving incompressible Navier–Stokes equations is demonstrated through the simulation of laminar flow past a circular cylinder that is placed in a channel. The solution obtained using the IB-PINN is compared with two reference solutions obtained using a conventional mesh-based IB method and an ordinary body-fitted grid method. The comparison indicates that the three solutions are in excellent agreement with each other. The influences of some parameters, such as weights for different loss components, numbers of collocation and marker points, hyperparameters in the neural network, etc., on the performance of IB-PINN are also studied. In addition, a transfer learning experiment is conducted on solving Navier–Stokes equations with different Reynolds numbers.

Application of finite volume particle method for axisymmetric modeling of droplet formation in dripping and Rayleigh regimes

An axisymmetric model has been developed in the finite volume particle method (FVPM). FVPM is a conservative, consistent, meshless particle method that incorporates properties of both smoothed particle hydrodynamics (SPH) and the mesh-based finite volume method (FVM). The surface tension effect amplifies capillary instability which is the main mechanism in dripping and jet disintegration. The simulations are performed in 2D cylindrical coordinates by only considering the liquid flow (one phase). The model is validated for free liquid droplet evolved from cylindrical state, dripping from a capillary tube, Rayleigh instability of capillary liquid cylinder columns, and Rayleigh breakup of viscous jets. The FVPM-predicted pressure and oscillating period are in good agreement with theoretical solution for a free droplet. The FVPM-computed dripping length shows good consistency with provided experimental data in literature. The predicted growth rate of capillary instability is in good agreement with analytical solutions for flows with different orders of Ohnesorge numbers. The numerical breakup length of jet with Weber numbers between 2.5 and 40 has been determined with good accuracy based on analytical experimental solution.

Bow shape modification through multi-objective hydrodynamic optimization: Methodology comparison between CAD-based FreeForm Deformation and Mesh-based Radial Basis Function approach

Marine industrial engineering face crucial challenges because of environmental footprint of vehicles, global recession, construction, and operation cost. Meanwhile, Shape optimization is the key feature to improve ship efficiency and ascertain better design. Accordingly, the present paper proposes an automated optimization framework for ship hullform modification to reduce total resistance at two cruise and sprint speeds. The case study is a bow shape of a wave-piercing bow trimaran hull. To this end, a multi-objective hydrodynamic problem needs to be solved. A combined optimization strategy using CFD hullform optimization is presented using the software tools STAR-CCM+ and SHERPA algorithm as optimizer. Furthermore, a comparison is made between CAD-based and Mesh-based parametrization techniques. Comparison between geometry regeneration methods is performed to present a practical and efficient parametrization tool. Design variables are control points of FreeForm Deformation (FFD) for CAD-based method and Radial Basis Function (RBF) for Mesh-based method. The optimization results show a 4.77% and 2.47% reduction in the total resistance at cruise and sprint speed, respectively.

Radial Force Density Calculation of Switched Reluctance Machines Using Reluctance Mesh-Based Magnetic Equivalent Circuit

Acoustic noise and vibration is one of the shortcomings of a switched reluctance machine (SRM). Harmonics of the radial force waveform in the airgap excite the stator structure at different vibration modes with specific frequencies. The radial force density in the airgap should be calculated before analyzing and mitigating acoustic noise and vibration. This paper proposes a reluctance mesh-based magnetic equivalent circuit (MEC) model to calculate the airgap radial force density. Reluctance mesh-based MEC models are developed for 3-phase 6/4, 6/16, 12/8 and 4-phase 8/6, 8/10, and 16/12 SRMs. A technique for the dynamic modeling of SRMs is proposed using the reluctance mesh-based MEC method. Dynamic currents are calculated using the proposed technique and, then, the radial and tangential flux density in the airgap are calculated. The radial force density in the airgap is calculated by applying the Maxwell Stress Tensor method. Fourier series is used to calculate the harmonics of the radial force density. The results obtained from the MEC model are verified using finite element method (FEM) models. The implemented MEC-based dynamic modeling method is validated using experimental results.

A multi-objective optimisation study of trimaran hull applying RBF-Morph technique and integrated optimisation platform at two design speeds

ABSTRACT This paper presents an efficient optimisation method to improve the main hull of a trimaran ship, whilst proposing a computational fluid dynamics-based automated approach to reduce total resistance. A mesh-based method is introduced to modify a wave-piercing bow trimaran hull at two cruise and sprint speeds. Therefore, the problem pertains to a hydrodynamic multi-objective optimisation problem. Radial basis function-based mesh-morphing tool is implemented to alter the geometry at the mesh level. Mesh-morphing tool leads to elimination of geometry and mesh regeneration steps that consequently provides a shortcut for the designer's extrication from optimisation time and complexity of geometry modification. Ten global parameters accomplish expansion and contraction of the 10 sections, which are known as Magnification Factor. Optimisation results and design comparison illustrate the applicability and efficiency of the proposed technique. The results demonstrate 6.77% reduction in total resistance at cruise speed and 1.55% at sprint speed.