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The purpose of this paper is to use different model order reduction techniques to cope with the computational effort of solving large systems of equations. By appropriate decomposition of the electromagnetic field problem, the number of degrees of freedom (DOF) can be efficiently reduced. In this contribution, the Proper Generalized Decomposition (PGD) and the Proper Orthogonal Decomposition (POD) are used in the frame of the T-Ω-formulation, and the feasibility is elaborated.

The POD and the PGD are two methods to reduce the model order. Particularly in the context of eddy current problems, conventional time-stepping algorithms can lead to many numerical simulations of the studied problem. To simulate the transient field, the T-Ω-formulation is used which couples the magnetic scalar potential and the electric vector potential. In this paper, both methods are studied on an academic example of an induction furnace in terms of accuracy and computational effort.

Using the proposed reduction techniques significantly reduces the DOF and subsequently the computational effort. Further, the feasibility of the combination of both methods with the T-Ω-formulation is given, and a fundamental step toward fast simulation of eddy current problems is shown.

In this paper, the PGD is combined for the first time with the T-Ω-formulation. The application of the PGD and POD and the following comparison illustrate the great potential of these techniques in combination with the T-Ω-formulation in context of eddy current problems.

The calculation of electromagnetic fields can involve many degrees of freedom (DOFs) to achieve accurate results. The DOFs are directly related to the computational effort of the simulation. The effort is decreased by using the proper generalized decomposition (PGD) and proper orthogonalized decomposition (POD). The purpose of this study is to combine the advantages of both methods. Therefore, a hybrid enrichment strategy is proposed and applied to different electromagnetic formulations.

The POD is an a-priori method, which exploits the solution space by decomposing reference solutions of the field problem. The disadvantage of this method is given by the unknown number of solutions necessary to reconstruct an accurate field representation. The PGD is an a-priori approach, which does not rely on reference solutions, but require much more computational effort than the POD. A hybrid enrichment strategy is proposed, based on building a small POD model and using it as a starting point of the PGD enrichment process.

The hybrid enrichment process is able to accurately approximate the reference system with a smaller computational effort compared to POD and PGD models. The hybrid enrichment process can be combined with the magneto-dynamic T-Ω formulation and the magnetic vector potential formulation to solve eddy current or non-linear problems.

The PGD enrichment process is improved by exploiting a POD. A linear eddy current problem and a non-linear electrical machine simulation are analyzed in terms of accuracy and computational effort. Further the PGD-AV formulation is derived and compared to the PGD-T-Ω reduced order model.

This paper aims to elaborate a set of characteristics that conceptualize and qualify a disruptive business model.

The literature on disruptive business models will be analyzed using the latent semantic analysis (LSA) technique, complemented by content analysis, to obtain a more precise qualification and conceptualization regarding disruptive business models.

The results found described concepts already described in the theory. However, such findings, highlighted by the LSA, bring new perspectives to the analysis of the disruptive business models, little discussed in the literature and which reveal important considerations to be made on this subject.

It should be noted, about the technique used, a limitation on the choice of the number of singular values. For this to be a problem in the open literature, the authors tried to work not just with the cost-benefit ratio given the addition of each new dimension in the analysis, as well as a criterion of saturation of the terms presented.

The presentation of this set of characteristics can be used as a validation tool to identify if a business is or is not a disruptive business model by managers.

The originality of this paper is the achievement of a consolidated set of characteristics that conceptualize and qualify the disruptive business models by conducting an in-depth analysis of the literature on disruptive business models through the LSA technique, considering the difficulty of obtaining precise concepts on this subject in the literature.

This article seeks to explain how to monitor the chronic obstructive disease patient and control any complications so that timely treatment can be applied.

Control charts and statistical process control (SPC) theory were used on chronic respiratory patient follow‐up and control. Controlling several variables simultaneously, using univariate charts, can be misleading, more so when there are correlated variables, so multivariate and univariate control charts were studied.

One‐sided control charts are preferable when the aim is to detect changes in the mean solely in one direction. Thus, one‐sided, univariate and multivariate charts were built, which identified previously undetected out‐of‐control events.

The study's main limitation is its retrospective nature. However, following‐up individual patients can highlight medical therapy effects.

The article concludes that control charts, in particular one‐sided ones, are a valuable tool for monitoring chronic respiratory patients, thus contributing to medical decision making.

The article highlights control chart application to chronic respiratory patient follow‐up, permitting a global view of patient evolution over time.

This study aims to investigate the effects of electroactive morphing on the Airbus A320 Reduced Scale prototype of the H2020 N° 723402 European Research project smart morphing and sensing (SMS) for aeronautical configurations [1]^,[2].

The flow regimes correspond to low subsonic take-off conditions. The morphing is applied through the vibration and slight deformation of the near trailing edge region; respecting the way, this actuation has been applied on the experimental prototype using micro fibre composite actuators. Optimal frequency range has been used, associated with low amplitudes of deformation with the Arbitrary Lagrangian Eulerian methodology. This study used an adapted turbulence modelling with the organised eddy simulation (OES) as well as a hybrid approach delayed detached eddy simulation – with embedded OES (DDES–OES), able to sensitise and keep up the coherent structures development.

The morphing at an optimal frequency (300 Hz) and amplitude (0.7 mm), applied on a length (3.5 cm) near the trailing edge, has been studied at Reynolds number 1 million and incidence of 10°. The effects on the main flow instabilities and on the turbulent vortex structures are analysed using proper orthogonal decomposition. A modification of the wake structures and a formation of organised rows of vortices along the shear layer are obtained. This leads to a quasi-two-dimensional wake, benefits on the aerodynamic performance and a decrease of the frequency peaks in the spectrum, corresponding to an attenuation of the coherent structures.

This study provides a fundamental understanding of how the actuation modifies the coherent and turbulent vortex structures around the wing and in the wake.

This paper seeks to present a novel computational intelligence technique to generate concise neural network models for distributed dynamic systems.

The approach used in this paper is based on artificial neural network architectures that incorporate linear and nonlinear principal component analysis, combined with generalized dimensional analysis.

Neural network principal component analysis coupled with generalized dimensional analysis reduces input variable space by about 90 percent in the modeling of oil reservoirs. Once trained, the computation time is negligible and orders of magnitude faster than any traditional discretisation schemes such as fine‐mesh finite difference.

Finding the minimum number of input independent variables needed to characterize a system helps in extracting general rules about its behavior, and allows for quick setting of design guidelines, and particularly when evaluating changes in the physical properties of systems.

The methodology can be used to simulate dynamical systems characterized by differential equations, in an interactive CAD and optimization providing faster on‐line solutions and speeding up design guidelines.

The aim of this paper is to develop a redundancy‐resolution (RR) algorithm to optimize the joint space trajectory of the six‐rotation‐axis industrial robot as performing arc‐welding tasks.

The rotation of the tool around its symmetry axis is clearly irrelevant to the view of the task to be accomplished besides some exceptional situations. When performed with a general 6‐degrees‐of‐freedom (DOF) manipulator, there exists one DOF of redundancy that remains. By taking advantage of the symmetry axis of the welding electrode, the authors decompose the required instantaneous twist of the electrode into two orthogonal components, one lying into the relevant task subspace and one into the redundant task subspace, respectively. Joint‐limits and singularity avoidance are considered as the optimization objectives.

The twist‐decomposition algorithm is able to optimize effectively the joint space trajectory. It has been tested and demonstrated in simulation.

A new RR algorithm is introduced for the six‐rotation‐axis industrial robot performing welding tasks. A new kinetostatic performance index is proposed on evaluating the kinematic quality of robotic postures. It can also be used in other applications like milling, deburing and many other tasks requiring less than 6‐DOF in tool frame.

This paper aims to improve the infilling efficiency and the quality of parts forming. It proposes two improved scanning path planning algorithm based on velocity orthogonal decomposition.

The algorithms this paper proposes replace empty paths and corners with circular segments, driving each axis synchronously according to the SIN or COS velocity curve to make the extruder always moves at a constant speed at maximum during the infilling process. Also, to support the improved algorithms, a three-dimensional (3D) printing control system based on circular motion controller is also designed.

The simulation and experiment results show that the improved algorithms are effective, and the printing time is shortened more significantly, especially in the case of small or complex models. What’s more, the optimized algorithm is not only compact in shape but also not obvious in edge warping.

The algorithms in this paper are not applicable to traditional motion controllers.

The algorithms in this paper improve the infilling efficiency and the quality of parts forming.

There are no social implications in this paper.

The specific optimization method of parallel-line scanning algorithm based on velocity orthogonal decomposition is replacing the empty paths with arc corners. And the specific optimization method of contour offsetting algorithm based on velocity orthogonal decomposition is to add connection paths between adjacent contours and turn all straight corners into arcs. What’s more, the 3D printing control system based on the circular motion controller can achieve multi-axis parallel motion to support these two improved path scanning algorithms.

The current paper aims to develop a reduced order discontinuous Galerkin method for solving the generalized Swift–Hohenberg equation with application in biological science and mechanical engineering. The generalized Swift–Hohenberg equation is a fourth-order PDE; thus, this paper uses the local discontinuous Galerkin (LDG) method for it.

At first, the spatial direction has been discretized by the LDG technique, as this process results in a nonlinear system of equations based on the time variable. Thus, to achieve more accurate outcomes, this paper uses an exponential time differencing scheme for solving the obtained system of ordinary differential equations. Finally, to decrease the used CPU time, this study combines the proper orthogonal decomposition approach with the LDG method and obtains a reduced order LDG method. The circular and rectangular computational domains have been selected to solve the generalized Swift–Hohenberg equation. Furthermore, the energy stability for the semi-discrete LDG scheme has been discussed.

The results show that the new numerical procedure has not only suitable and acceptable accuracy but also less computational cost compared to the local DG without the proper orthogonal decomposition (POD) approach.

The local DG technique is an efficient numerical procedure for solving models in the fluid flow. The current paper combines the POD approach and the local LDG technique to solve the generalized Swift–Hohenberg equation with application in the fluid mechanics. In the new technique, the computational cost and the used CPU time of the local DG have been reduced.

We present a new approach to spectrum estimation leading to computationally efficient high‐resolution estimator. Our approach is based on the orthogonal sum decomposition, and this could be viewed as weighted periodograms averaging.