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The purpose of this paper is to develop a fast and accurate analytic model function for the single-valued H-B curve of ferromagnetic materials, where hysteresis can be disregarded (normal magnetization curve). Nonlinear magnetoquasistatic simulations demand smooth monotone material models to ensure physical correctness and good convergence in Newton's method.

The Brauer model has these beneficial properties, but is not sufficiently accurate for low and high fields in the normal magnetization curve. The paper extends the Brauer model to better fit material behavior in the Rayleigh region (low fields) and in full saturation. Procedures for obtaining optimal parameters from given measurement points are proposed and tested for two technical materials. The approach is compared with cubic spline and monotonicity preserving spline interpolation with respect to error and computational effort.

The extended Brauer model is more accurate and even maintains the computational advantages of the classical Brauer model. The methods for obtaining optimal parameters yield good results if the measurement points have a distinctive Rayleigh region.

The model function for ferromagnetic materials enhances the precision of the classical Brauer model without notable additional simulation cost.

The purpose of this paper is to present the applicability of data-driven solvers to computationally demanding three-dimensional problems and their practical usability when using real-world measurement data.

Instead of using a hard-coded phenomenological material model within the solver, the data-driven computing approach reformulates the boundary value problem such that the field solution is directly computed on raw measurement data. The data-driven formulation results in a double minimization problem based on Lagrange multipliers, where the sought solution must conform to Maxwell’s equations while at the same time being as close as possible to the available measurement data. The data-driven solver is applied to a three-dimensional model of a direct current electromagnet.

Numerical results for data sets of increasing cardinality verify that the data-driven solver recovers the conventional solution. Additionally, the practical usability of the solver is shown by using real-world measurement data. This work concludes that the data-driven magnetostatic finite element solver is applicable to computationally demanding three-dimensional problems, as well as in cases where a prescribed material model is not available.

Although the mathematical derivation of the data-driven problem is well presented in the referenced papers, the application to computationally demanding real-world problems, including real measurement data and its rigorous discussion, is missing. The presented work closes this gap and shows the applicability of data-driven solvers to challenging, real-world test cases.

Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many tropical countries are expected to be the most areas affected by accelerated climate change and global warming, which may have a severe impact on labour health and productivity. The purpose of this paper is to assess whether the existing models can be used to predict labour productivity based on weather conditions in the tropics.

Five models are identified from the literature for evaluation. Using real labour productivity data of a high-rise building project in Malaysia, the actual productivity rate was compared with predicted productivity rates generated using the five models. The predicted productivity rates were generated using weather variables collected from an adjusting weather station to the project.

Compared with other models evaluated in this paper, the United States Army Corps of Engineers (USACE) was found to be the best model to predict productivity based on the case study data. However, the result shows only a 57% accuracy level of the USACE model indicating the need to develop a new model for the tropics for more accurate prediction.

The result of this study is perhaps the first to apply meteorological variables to predict productivity rates and validate them using actual productivity data in the tropics. This study is the first step to developing a more accurate productivity model, which will be useful for project planning and more accurate productivity rate estimation.

Our physical universe is 1.5×10¹⁰ years old. It began with the Big Bang. There is some debate about what happened in the first tenth of a second! The first 3×10⁵ years were radiation dominated. Since then it has been matter dominated. (This in accordance with the first law of thermodynamics which states that total mass-energy is conserved.) The universe has continuously expanded in space and in the future either this may continue, or expansion may stabilise at a fixed size or the universe may contract in the Big Crunch (depending on the spatial curvature). At a certain scale the universe is spatially isotropic and homogeneous. Its trajectory exhibits increasing entropy in accordance with the second law of thermodynamics. These statements are in accordance with certain models and empirical data: distant galaxies are receding from us at a velocity proportional to their distance; there is greater spatial uniformity at greater distances from us; there is uniform presence in space of radiation with a temperature of 2.7K; etc.

Today, industrial revolutions demands advanced technologies, means, mediums, tactics and so forth for optimizing their operating behavior and opportunities. It is probed that the effectual results can be seized into system by not only developing advance means and technologies, but also capably adapting these developed technologies, their user interface and their utilization at optimum levels. Today, industrial resources need perfect synchronization and optimization for getting elevated results. Accordingly, present study is furnished with the purpose to expose quality-driven insights to march toward excellence by optimizing existing resources by the industrial organizations. The present study evaluates quality attributes of mechanical machineries for seizing performance opportunities and maintaining competitiveness via synchronizing and reconfiguring firm's resources under quality management system.

In the present study, Kano’s integrated approach is implemented for supporting decision rational concerning industrial assets. The integrative Kano–analytic hierarchy process (AHP) approach is used to reflect the relative importance of quality attributes. Kano and AHP tactics are integrated to define global relative weight and their computational medium is adapted along with ratio analysis, reference point theory and TOPSIS technique for understanding robust decision. The study described an interesting idea for underpinning quality attributes for benchmarking system substitutes. A machine tool selection case is discussed to disclose the significant aspect of decision-making and its virtual qualities.

The decision executives can realize massive benefits by streaming quality data, advanced information, technological advancements, optimum analysis and by identifying quality measures and disruptions for gaining performance deeds. The study determined quality measures for benchmarking machine tool substitute for industrial applications. Momentous machine alternatives are evaluated by means of technical structure, dominance theory and comparative analysis for supporting decision-making of industrial assets based on optimization and synchronization.

The study linked financial, managerial and production resources under sole platform to present a technical structure that may assist in improving the performance of the manufacturing firms. The study provides a decision support mechanism to assist in reviewing the momentous resources to imitate a higher level of productive strength toward the manufacturing firms. The study endeavors its importance toward optimizing resources, which is an evident requirement in industries as the same not only saves money, escalates production, improves profit margins and so forth, but also gratifies the consumption of scarce natural resources.

The study stressed that advance information can be sought from system characteristics in the form of quality measures and attributes, which can be molded for gaining elevated outcomes from existing system characteristics. The same demands decision supports tools and frameworks to utilize data-driven information for benchmarking operations and supply chain activities. The study portrayed an approach for ease of utilizing data-driven information by the decision-makers for demonstrating superior outcomes. The study originally conceptualized multi-attributes appraisement framework associated with subjective cum objective quality measures to evaluate the most significant machine tool choice amongst preferred alternatives.

Traditional epidemic models, like the classical SIR, are fitted to real data using deterministic optimization techniques. As a consequence, their performances cannot be properly assessed and, more importantly, the estimates of the critical epidemic parameters (which are of dramatic importance in monitoring the epidemic evolution) cannot be complemented with the calculation of confidence intervals. The aim of the present work is to remove such limitations and to compare the results obtained using two stochastic versions of deterministic SIR models. We describe the two alternatives and the associated estimation procedures, and we apply the two methodologies to a set of COVID-19 data observed in Italy in the 2020 pandemic wave. Our estimates of the basic reproduction number are comparable with the official sources, but using our methods uncertainty can also be properly assessed.

Purpose – The chapter reports on an attempt to compute the size of gross world product (GWP) under the assumption that all violence ceases.

Methodology/approach – Spreadsheet-based simulations, given seed values taken from extensive literature review; this is done, for 2007, in nominal foreign exchange–based US dollars (USD) as well as in purchasing power parity (ppp)–based dollars (international dollars).

Beneficial economic effects from more internal peace (nonviolence within countries) as well from external peace (nonviolence between and among countries) are calculated for each of 140 countries. In addition, we compute sectoral economic effects for the United States.

Findings – For 2007, the simulations suggest that in a state of nonviolence the world economy could have been larger by 4.8 trillion dollars, or 8.7 per cent of actual GWP, when measured in nominal, foreign exchange–based USD, or by 6.0 trillion international dollars, or 9.2 per cent of GWP, when measured in purchasing power parity values.

Limitations – The simulations are based on disparate values found in the literature to seed the spreadsheet calculations; various assumptions are made that would need to be confirmed through country- and sector-specific studies.

Practical implications – Knowledge of the potential size of forgone economic benefits due to violence can assist to set out global violence reduction goals in order to achieve measurable economic results.

Originality/value of chapter – To our knowledge this is the first attempt to calculate the size of the worldwide economic benefits forgone due to violence.

Universities across the USA are facing challenging decision-making problems amid the COVID-19 pandemic. The purpose of this study is to facilitate universities in planning disease mitigation interventions as they respond to the pandemic.

An agent-based model is developed to mimic the virus transmission dynamics on campus. Scenario-based experiments are conducted to evaluate the effectiveness of various interventions including course modality shift (from face-to-face to online), social distancing, mask use and vaccination. A case study is performed for a typical US university.

With 10%, 30%, 50%, 70% and 90% course modality shift, the number of total cases can be reduced to 3.9%, 20.9%, 35.6%, 60.9% and 96.8%, respectively, comparing against the baseline scenario (no interventions). More than 99.9% of the total infections can be prevented when combined social distancing and mask use are implemented even without course modality shift. If vaccination is implemented without other interventions, the reductions are 57.1%, 90.6% and 99.6% with 80%, 85% and 90% vaccine efficacies, respectively. In contrast, more than 99% reductions are found with all three vaccine efficacies if mask use is combined.

This study provides useful implications for supporting universities in mitigating transmissions on campus and planning operations for the upcoming semesters.

An agent-based model is developed to investigate COVID-19 transmissions on campus and evaluate the effectiveness of various mitigation interventions.

This paper aims to create a conceptual model that connects learning organizations, service innovation and technology acceptance.

The importance of the interaction of variables benefiting both individuals and organizations has been comprehensively explained by combining two well-known theories – learning organizational theory and service innovation theory – with the technology acceptance model. In the first part of the study, conceptual model has been constructed and then applied to the hospitality industry of which results have been presented in the second part of this paper.

It is hypothesized that learning organization, service innovation and technology acceptance have significant relationships. It is also suggested that the learning organization plays an intermediary role in the relationship between technology acceptance and service innovation. Empirical results in this regard have been presented in the second part of the paper.

The relations have been established and tested in the hospitality industry in Antalya. However, the model can be applied and established relations tested in other industries.

This research contributes to our knowledge of the intricate linkages that exist between learning organizations, technology acceptance and service innovation. Originality of the paper is related to the novel multilayered model illustrating three-way interactions between the three dimensions of learning organization, technology acceptance and service innovation.

The purpose of this paper is the derivation and efficient implementation of surface impedance boundary conditions (SIBCs) for nonlinear magnetic conductors.

An approach based on perturbation theory is proposed, which expands to nonlinear problems the methods already developed by the authors for linear problems. Differently from the linear case, for which the analytical solution of the diffusion equation in the semi-infinite space for the magnetic field is available, in the nonlinear case the corresponding nonlinear diffusion equation must be solved numerically. To this aim, a suitable smooth map is defined to reduce the semi-infinite computational domain to a finite one; then the diffusion equation is solved by a Galerkin method relying on basis functions constructed via the push-forward of a Lagrangian polynomial basis whose degrees of freedom are collocated at Gauss–Lobatto nodes. The use of such basis in connection with a suitable under-integration naturally leads to mass-lumping without impacting the order of the method. The solution of the diffusion equation is coupled with a boundary element method formulation for the case of parallel magnetic conductors in terms of E and B fields.

The results are validated by comparison with full nonlinear finite element method simulations showing very good accordance at a much lower computational cost.

Limitations of the method are those arising from perturbation theory: the introduced small parameter must be much less than one. This implies that the penetration depth of the magnetic field into the magnetic and conductive media must be much smaller than the characteristic size of the conductor.

The efficient implementation of a nonlinear SIBC based on a perturbation approach is proposed for an electric and magnetic field formulation of the two-dimensional problem of current driven parallel solid conductors.