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This study aims to derive a novel spatial numerical method based on multidimensional local Taylor series representations for solving high-order advection-diffusion (AD) equations.

The parabolic AD equations are reduced to the nonhomogeneous elliptic system of partial differential equations by utilizing the Chebyshev spectral collocation method (ChSCM) in the temporal variable. The implicit-explicit local differential transform method (IELDTM) is constructed over two- and three-dimensional meshes using continuity equations of the neighbor representations with either explicit or implicit forms in related directions. The IELDTM yields an overdetermined or underdetermined system of algebraic equations solved in the least square sense.

The IELDTM has proven to have excellent convergence properties by experimentally illustrating both h-refinement and p-refinement outcomes. A distinctive feature of the IELDTM over the existing numerical techniques is optimizing the local spatial degrees of freedom. It has been proven that the IELDTM provides more accurate results with far fewer degrees of freedom than the finite difference, finite element and spectral methods.

This study shows the derivation, applicability and performance of the IELDTM for solving 2D and 3D advection-diffusion equations. It has been demonstrated that the IELDTM can be a competitive numerical method for addressing high-space dimensional-parabolic partial differential equations (PDEs) arising in various fields of science and engineering. The novel ChSCM-IELDTM hybridization has been proven to have distinct advantages, such as continuous utilization of time integration and optimized formulation of spatial approximations. Furthermore, the novel ChSCM-IELDTM hybridization can be adapted to address various other types of PDEs by modifying the theoretical derivation accordingly.

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 investigates income convergence using different convergence concepts and methodologies for 72 countries over the period between 1960 and 2010.

This study applies beta (β), sigma (s), stochastic and club convergence approaches. For β-convergence analysis, it derives the cross-country growth regressions of the Solow growth model under the basic and augmented Cobb–Douglass (CD) production functions and estimates them using cross-section and panel data estimators. While it employs both the widely used coefficient of variation and recently developed weak s-convergence approaches for s-convergence, it applies three different unit root tests for stochastic convergence. To test club convergence, it estimates the log-t regression.

The results reveal that (1) there exists conditional β-convergence, meaning that poorer countries grow faster than richer countries; (2) income per worker is not (weakly) s-converging, and cross-sectional variation does not tend to fall over the years; (3) stochastic convergence is not found and (4) countries in the sample do not converge to the unique equilibrium, and there exist five distinctive convergence clubs.

The results clearly show that heavily relying on one of the convergence techniques might lead researchers to obtain misleading results regarding the existence of convergence. Therefore, to draw reliable inferences, the results should be checked using different convergence concepts and methodologies.

Contrary to the previous literature, which is generally restricted to testing the existence of absolute and conditional β-convergence between countries, to the best of the author’s knowledge, this is the first study to consider and compare all originally and recently developed fundamental concepts of convergence altogether. Besides, it uses the Penn World Table (PWT) 9.1 and extends the period to 2010. From this point of view, this study is believed to provide the most up-to-date empirical evidence.

The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system.

The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively.

From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system.

Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

We revisit the problem of redesigning the Master in Business Administration (MBA) program, curriculum, and pedagogy, focusing on understanding and seeking to tame its “wicked problems,” as an intrinsic part and challenge of the MBA program venture, and to render it more realistic and relevant to address major problems and their consequences. We briefly review the theory of wicked problems and methods of dealing with their consequences from multiple perspectives. Most characterization of problems classifies them as simple (problems that have known formulations and solutions), complex (where formulations are known but not their resolutions), unstructured problems (where formulations are unknown, but solutions are estimated), and “wicked” (where both problem formulations and their resolutions are unknown but eventually partially tamable). Uncertainty, unpredictability, randomness, and ambiguity increase from simple to complex to unstructured to wicked problems. A redesigned MBA program should therefore address them effectively through the four semesters in two years. Most of these problems are real and affect life and economies, and hence, business schools cannot but incorporate them into their critical, ethical, and moral thinking.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

Traditional case-adaptation methods have poor accuracy, low efficiency and limited applicability, which cannot meet the needs of knowledge users. To address the shortcomings of the existing research in the industry, this paper proposes a case-adaptation optimization algorithm to support the effective application of tacit knowledge resources.

The attribute simplification algorithm based on the forward search strategy in the neighborhood decision information system is implemented to realize the vertical dimensionality reduction of the case base, and the fuzzy C-mean (FCM) clustering algorithm based on the simulated annealing genetic algorithm (SAGA) is implemented to compress the case base horizontally with multiple decision classes. Then, the subspace K-nearest neighbors (KNN) algorithm is used to induce the decision rules for the set of adapted cases to complete the optimization of the adaptation model.

The findings suggest the rapid enrichment of data, information and tacit knowledge in the field of practice has led to low efficiency and low utilization of knowledge dissemination, and this algorithm can effectively alleviate the problems of users falling into “knowledge disorientation” in the era of the knowledge economy.

This study provides a model with case knowledge that meets users’ needs, thereby effectively improving the application of the tacit knowledge in the explicit case base and the problem-solving efficiency of knowledge users.

The adaptation model can serve as a stable and efficient prediction model to make predictions for the effects of the many logistics and e-commerce enterprises' plans.

This study designs a multi-decision class case-adaptation optimization study based on forward attribute selection strategy-neighborhood rough sets (FASS-NRS) and simulated annealing genetic algorithm-fuzzy C-means (SAGA-FCM) for tacit knowledgeable exogenous cases. By effectively organizing and adjusting tacit knowledge resources, knowledge service organizations can maintain their competitive advantages. The algorithm models established in this study develop theoretical directions for a multi-decision class case-adaptation optimization study of tacit knowledge.

Beginners and even experienced ones have difficulties in completing the structural fire analysis due to numerical difficulties such as convergence errors and singularity and have to spend a lot of time making many repetitive changes on the model. The aim of this article is to highlight the advantages of explicit solver which can eliminate the mentioned difficulties in finite element analysis containing highly nonlinear contacts, clearance between modeled parts at the beginning and large deflections because of high temperature. This article provides important information, especially for researchers and engineers who are new to structural fire analysis.

The finite element method is utilized to achieve mentioned purposes. First, a comparative study is conducted between implicit and explicit solvers by using Abaqus. Then, a validation process is carried out to illustrate the explicit process by using sequentially coupled heat transfer and structural analysis.

Explicit analysis offers an easier solution than implicit analysis for modeling multi-bolted connections under high temperatures. An optimum mesh density for bolted connections is presented to reflect the realistic structural behavior. Presented explicit process with the offered mesh density is used in the validation of an experimental study on multi-bolted splice connection under ISO 834 standard fire curve. A good agreement is achieved.

What makes the study valuable is that the points to be considered in the structural fire analysis are examined and it is a guide that future researchers can benefit from. This is especially true for modeling and analysis of multi-bolted connections in finite element software under high temperatures. The article can help to shorten and even eliminate the iterative debugging phases, which is a problematic and very time-consuming process for many researchers.

Adsorption parameters (e.g. Langmuir constant, mass transfer coefficient and Thomas rate constant) are involved in the design of aqueous-media adsorption treatment units. However, the classic approach to estimating such parameters is perceived to be imprecise. Herein, the essential features and performances of the ant colony, bee colony and elephant herd optimisation approaches are introduced to the experimental chemist and chemical engineer engaged in adsorption research for aqueous systems. Key research and development directions, believed to harness these algorithms for real-scale water treatment (which falls within the wide-ranging coverage of the Sustainable Development Goal 6 (SDG 6) ‘Clean Water and Sanitation for All’), are also proposed. The ant colony, bee colony and elephant herd optimisations have higher precision and accuracy, and are particularly efficient in finding the global optimum solution. It is hoped that the discussions can stimulate both the experimental chemist and chemical engineer to delineate the progress achieved so far and collaborate further to devise strategies for integrating these intelligent optimisations in the design and operation of real multicomponent multi-complexity adsorption systems for water purification.

The purpose of this paper is to simulate the tension process of tension-type anchor cable and to explore the mechanical characteristics and tension-torsion coupling effect of anchor cable subjected to tension.

ABAQUS numerical software is applied to construct the numerical models of tension-type anchor cables with different diameters. Through explicit contact, the characteristics of contact between grouting body-anchor cable and grouting body-rock mass are determined. Confining pressure is applied to the model through surface pressure, and drawing force is applied to the model by displacement loading so as to simulate the tension process of the anchor cable.

The results show that the stress is transmitted in both axial and radial directions in the anchorage section and distributed in a cone. The shear stress in the grouting body is unevenly distributed, and its peak value increases with the rise in confining pressure and anchor cable diameter. The stress characteristics of torque and axial force are basically consistent and evenly distributed in the free section; they gradually decrease in the anchorage section. Due to the tension-torsion coupling effect, the internal stress characteristics of the anchor cable structure vary. On average, the anchorage performance of each anchor cable model is improved by 6.19%.

The proposed method of numerical modelling is effective in addressing the interface contact between the anchor cable and the grouting body and in solving the problem with convergence of calculation. Compared with the indoor test, this method is more suited to collecting the internal mechanical data of the anchor body.