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Manifold‐mapping (MM) is an efficient surrogate‐based optimization technique aimed at the acceleration of very time‐consuming design problems. In this paper we present two new variants of the original algorithm that make it applicable to a broader range of optimization scenarios.

The first variant is useful when the optimization constraints are expressed by means of functions that are very expensive to compute. The second variant endows the original scheme with a trust‐region strategy and the result is a much more robust algorithm.

Two practical optimization problems from electromagnetics eventually show that the proposed variants perform efficiently.

The original MM algorithm is extended with two new variants. Therefore, the MM approach is applicable to a much larger set of design situations.

This one-year qualitative study examined the role Culturally Sustaining Pedagogies (Paris, 2012; Paris & Alim, 2014) had on secondary pre-service teachers in an urban school. This study examined the journey of six pre-service urban high-school teachers in Arizona as they enact Culturally Sustaining Pedagogy (CSP) in a year-long student teaching residency. Pre-service teachers worked with and learned from English Language Learners in various contexts. Factors that influenced their CSP practices are discussed through themes that emerged from interviews and classroom observations.

The purpose of this work is to investigate the similarity requirements for the application of multifidelity modeling (MFM) for the prediction of airfoil dynamic stall using computational fluid dynamics (CFD) simulations.

Dynamic stall is modeled using the unsteady Reynolds-averaged Navier–Stokes equations and Menter's shear stress transport turbulence model. Multifidelity models are created by varying the spatial and temporal discretizations. The effectiveness of the MFM method depends on the similarity between the high- (HF) and low-fidelity (LF) models. Their similarity is tested by computing the prediction error with respect to the HF model evaluations. The proposed approach is demonstrated on three airfoil shapes under deep dynamic stall at a Mach number 0.1 and Reynolds number 135,000.

The results show that varying the trust-region (TR) radius (λ) significantly affects the prediction accuracy of the MFM. The HF and LF simulation models hold similarity within small (λ ≤ 0.12) to medium (0.12 ≤ λ ≤ 0.23) TR radii producing a prediction error less than 5%, whereas for large TR radii (0.23 ≤ λ ≤ 0.41), the similarity is strongly affected by the time discretization and minimally by the spatial discretization.

The findings of this work present new knowledge for the construction of accurate MFMs for dynamic stall performance prediction using LF model spatial- and temporal discretization setup and the TR radius size. The approach used in this work is general and can be used for other unsteady applications involving CFD-based MFM and optimization.

This work aims to present a multilevel optimization strategy based on manifold‐mapping combined with multiquadric interpolation for the coarse model construction.

In the proposed approach the coarse model is obtained by interpolating the fine model using multiquadrics in a small number of points. As the algorithm iterates the response surface model is improved by enriching the set of interpolation points.

This approach allows to accurately solve the TEAM Workshop Problem 25 using as little as 33 finite element simulations. Furthermore, it allows a robust sizing optimization of a cylindrical voice‐coil actuator with seven design variables.

Further analysis is required to gain a better understanding of the role that the initial coarse model accuracy plays in the convergence of the algorithm. The proposed model allows to carry out such analysis by varying the number of points included in the initial response surface model. The effect of the trust‐region stabilization in the presence of manifolds of equivalent solutions is also a topic of further investigations.

Unlike the closely related space‐mapping algorithm, the manifold‐mapping algorithm is guaranteed to converge to a fine model optimal solution. By combining it with multiquadric response surface models, its applicability is extended to problems for which other kinds of coarse model such as lumped parameter approximations for instance are tedious or impossible to construct.

The space‐mapping (SM) optimization technique, with its input, implicit or output mapping‐based implementations, provides a basis for computationally efficient engineering optimization. Various algorithms and design optimization problems, related to microwave devices, antennas and electronic circuits, are presented in numerous publications. However, a new application area for SM optimization is currently expanding, i.e. the design of electromechanical actuators. The purpose of this paper is to present an overview of the recent developments.

New algorithm variants and their application to design problems in electromechanics and related fields are briefly summarized.

The paper finds that SM optimization offers a significant speed‐up of the optimization procedures for the design of electromechanical actuators. Its true potential in the area of magnetic systems and actuator design is still rather unexplored.

This overview is complementary to the previous published reviews and shows that the application of SM optimization has also extended to the design of electromechanical devices.

This paper aims to report how one can assess the transient stability of a power system by using stacked auto-encoders.

The proposed algorithm works in a power system equipped with the wide area measurement system. To be more exact, it needs pre- and post-disturbance values of frequency sent from phasor measurement units.

The authors have investigated the performance of the proposed method. Going through details, the authors have simulated many contingencies, and then have predicted the transient stability in each of which by using the proposed algorithm.

The results demonstrate that the algorithm is fast, and it has acceptable performance under different circumstances including the change of system topology and failures of telecommunication channels.

Optimisation in electromagnetics, based on finite element models, is often very time‐consuming. In this paper, we present the space‐mapping (SM) technique which aims at speeding up such procedures by exploiting auxiliary models that are less accurate but much cheaper to compute.

The key element in this technique is the SM function. Its purpose is to relate the two models. The SM function, combined with the low accuracy model, makes a surrogate model that can be optimised more efficiently.

By two examples we show that the SM technique is effective. Further we show how the choice of the low accuracy model can influence the acceleration process. On one hand, taking into account more essential features of the problem helps speeding up the whole procedure. On the other hand, extremely simple auxiliary models can already yield a significant acceleration.

Obtaining the low accuracy model is not always straightforward. Some research could be done in this direction. The SM technique can also be applied iteratively, i.e. the auxiliary model is optimised aided by a coarser one. Thus, the generation of hierarchies of models seems to be a promising venue for the SM technique.

Optimisation in electromagnetics, based on finite element models, is often very time‐consuming. The results given show that the SM technique is effective for speeding up such procedures.

The aim of this paper is to reduce the evaluations number of the fine model within the output space mapping (OSM) technique in order to reduce their computing time.

In this paper, n-level OSM is proposed and expected to be even faster than the conventional OSM. The proposed algorithm takes advantages of the availability of n models of the device to optimize, each of them representing an optimal trade-off between the model error and its computation time. Models with intermediate characteristics between the coarse and fine models are inserted within the proposed algorithm to reduce the number of evaluations of the consuming time model and then the computing time. The advantages of the algorithm are highlighted on the optimization problem of superconducting magnetic energy storage (SMES).

A major computing time gain equals to three is achieved using the n-level OSM algorithm instead of the conventional OSM technique on the optimization problem of SMES.

The originality of this paper is to investigate several models with different granularities within OSM algorithm in order to reduce its computing time without decreasing the performance of the conventional strategy.

The purpose of this paper is to present detailed algorithms for simulation of individual and group control of production wells in hydrocarbon reservoirs which are implemented in a finite volume-based reservoir simulator.

The algorithm for individual control is described for the multi-lateral multi-connection ones based on the multi-segment model considering cross-flow. Moreover, a general group control algorithm is proposed which can be coupled with any well model that can handle a constraint and returns the flow rates. The performance of oil production process based on the group control criteria is investigated and compared for various cases.

The proposed algorithm for group control of production wells is a non-optimization iterative scheme converging within a few number of iterations. The numerical results of many computer runs indicate that the nominal power of the production wells, in general, is the best group control criterion for the proposed algorithm. The production well group control with a proper criterion can generally improve the oil recovery process at negligible computational costs when compared with individual control of production wells.

Although the group control algorithm is implemented for both production and injection wells in the developed simulator, the numerical algorithm is here described only for production wells to provide more details.

The proposed algorithm can be coupled with any well model providing the fluid flow rates and can be efficiently used for group control of production wells. In addition, the calculated flow rates of the production wells based on the group control algorithm can be used as candidate solutions for the optimizer in the simulation-optimization models. It may reduce the total number of iterations and consequently the computational cost of the simulation-optimization models for the well control problem.

A complete and detailed description of ingredients of an efficient well group control algorithm for the hydrocarbon reservoir is presented. Five group control criteria are extracted from the physical, geometrical and operating conditions of the wells/reservoir. These are the target rate, weighted potential, ultimate rate and introduced nominal power of the production wells. The performance of the group control of production wells with different group control criteria is compared in three different oil production scenarios from a black-oil and highly heterogeneous reservoir.

The purpose of this paper is to investigate the use of multidisciplinary optimization (MDO) formulations within space‐mapping techniques in order to reduce their computing time.

The aim of this work is to quantify the interest of using MDO formulations within space mapping techniques. A comparison of three MDO formulations is carried out in a short time by using an analytical model of a safety transformer. This comparison reveals the advantage of two formulations in terms of robustness and computing time among the three MDO formulations. Then, the best formulations are investigated within output space mapping, using both analytical and FE models of the transformer.

A major computing time gain equal to 5.5 is achieved using the Individual Disciplinary Feasibility formulation within the output space‐mapping technique in the case of the safety transformer.

The MultiDisciplinary Feasibility formulation is the common formulation used within space‐mapping technique because it is the most conventional way to perform MDO. The originality of this paper is to investigate the Individual Disciplinary Feasibility formulation within output space‐mapping technique in order to allow the parallelization of calculation and to achieve a major reduction of computing time.