Search results

Global optimization in electrical engineering using stochastic methods requires usually a large amount of CPU time to locate the optimum, if the objective function is calculated either with the finite element method (FEM) or the boundary element method (BEM). One approach to reduce the number of FEM or BEM calls using neural networks and another one using multiquadric functions have been introduced recently. This paper compares the efficiency of both methods, which are applied to a couple of test problems and the results are discussed.

The conventional starting point for the design of an electrical machine (or any low-frequency electromagnetic device) is known as “sizing”. In this process, a simple magnetic circuit is used to estimate the main geometric parameters. This does not work for many devices, particularly where eddy currents and non-linearity dominate. The purpose of this paper is to investigate an approach using a neural network trained on a large database of existing designs as a general sizing system.

The approach is based on a combination of a radial basis function neural network and a database of stored performances of electrical machines. The network is trained based on a set of typical performance requirements for a machines design problem. The resulting design is analyzed using finite elements to determine if the design performance is acceptable.

The number of neurons in the network was varied to determine the approximation and generalization capabilities. The finite element analysis showed that the network produced initial design parameters which resulted in an appropriate performance.

The research has looked at only one class of machine. Further work is needed on a range of machines to determine how effective the approach can be.

The approach can provide a good initial design and thus can reduce overall design time significantly.

The paper proposes a novel, fast and effective generalized approach to sizing low frequency electromagnetic devices.

This chapter captures the interrelatedness of sustainable production and consumption, which can be brought together in the concept of sustainable market exchange. The purpose of this chapter is to develop and present a framework of sustainable market exchange, including the key players, factors that influence sustainable behavior and issues that need to be addressed to achieve sustainable market exchange. The framework includes the ecological, economic, and social dimensions, while factors in the framework are classified into three groups: individual, relational, and societal. The sustainability spheres and stakeholders contribute to raising the importance of the phenomenon in the long run. The authors subsequently conduct an exploratory quantitative study to examine the features of the framework which is empirically examined from the perspective of one group of stakeholders that needs to be understood better, that is, consumers. Searching for answers to research questions on how consumers perceive their sustainable behavior, company sustainable behavior, how perceptions of production and consumption are related and what are the differences according to individual factors, the authors demonstrate different emphasis that consumers place on different sustainability dimensions and suggest recommendations for encouraging sustainable market exchange for management and public policy stakeholders.

Carbonate-based heterogeneous reacting systems are investigated for the applications of thermochemical carbon dioxide capture and energy storage. This paper aims to review recent progress in numerical modeling of thermal transport phenomena in such systems.

Calcium oxide looping is selected as the model carbonate-based reacting system. Numerical models coupling heat and mass transfer to chemical kinetics are reviewed for solar-driven calcium oxide looping on the sorbent particle, particle bed, and reactor levels.

At the sorbent particle level, a transient numerical model of heat and mass transfer coupled to chemical kinetics has been developed for a single particle undergoing cyclic calcination and carbonation driven by time-periodic boundary conditions. Modeling results show cycle times impact the maximum sorbent utilization and solar-to-chemical energy efficiency. At the reactor level, a model of heat and mass transfer coupled to chemical kinetics of calcination of a packed-bed reactor concept has been developed to estimate the reactor’s performance. The model was used to finalize reactor geometry by evaluating pressure drops, temperature distributions, and heat transfer in the reactor.

Successful solar thermochemical reactor designs maximize solar-to-chemical energy conversion by matching chemical kinetics to reactor heat and mass transfer processes. Modeling furthers the understanding of thermal transport phenomena and chemical kinetics interactions and guides the design of solar chemical reactors.

Many engineering optimisation problems are difficult to describe mathematically and as such can not be easily optimised. Recently attention has focussed on developing methods to create approximations of the real object function using numerical model data instead. The approximated function can then be optimised using a suitable optimisation method. This paper describes the extraction of derivative information from a neuro‐fuzzy system. Subsequently, this permits the application of classic deterministic optimisation methods in order to identify the global minimum of any approximated objective function. For non‐differentiable functions this approach is of great benefit. Results from an analytical optimisation example, in which the objective function and the solution are known, and a two variable loudspeaker optimisation problem are discussed. In both cases, the neuro‐fuzzy system worked well to model the physical problem and the extracted derivative served to locate the minimum.

THE Corsair (U S Navy F4U‐1) is a single‐seater deck‐landing fighter. Like most American ship‐planes it has folding wings. The first single‐seater to be built by this company, its general resemblance in line to the Kingfisher and Chesapeake, particularly in the shape of the tail unit, is quite striking

This article compares consumer decision‐making styles between Singaporeans and Australians. Utilising Hofstede’s framework, the paper argues that cultural dimensions influence consumer decision making styles. It is essential that managers understand cross‐cultural consumer decision‐making styles to make strategic decisions or effectively handle members of these nationalities. Marked differences were found between the two populations for: brand consciousness, innovativeness and overchoice confusion. The results suggest that some consumer decision‐making styles differ due to consumers’ cultural values. Managerial implications and future research directions are discussed.

When several machine tools are serviced by one industrial robot their idle times should be kept as short as possible. In this paper, a deterministic model is developed to optimise the idle time, including the possibility of machine breakdowns.

This paper analyses the voice of customers (VoCs) using a hybrid clustering multi-criteria decision-making (MCDM) approach. The proposed method serves as an efficient tool for how to approach multiple decision-making involving a large set of countrywide customer complaints in the Iranian automotive sector.

The countrywide data comprising 3,342 customer complaints (VoCs) were gathered. A total of seven determinant complaint criteria were identified in brainstorming sessions with three groups (six each) of experts employing the fuzzy Delphi method. The weights of these criteria were assigned by applying the fuzzy best–worst method (FBWM) to identify the severity of the complaints. Subsequently, the complaints were clustered into five categories with respective customer locations (province), car type and manufacturer using the K-mean method and further prioritised and ranked employing the fuzzy complex proportional assessment of alternatives (FCOPRAS) method.

The results indicated that the majority of complaints (1,027) from the various regions of the country belonged to one specific model of car made by a particular producer. The analyses revealed that only a few complaints were related to product quality, with the majority related to service and financial processes including delays in automobile delivery, delays in calculating monthly instalments, price variation, failure to provide a registration ( licence) and failure to supply the agreed product. The proposed method is an efficient way to solve large-scale multidimensional problems and provide a robust and reliable set of results.

The proposed method makes it much easier for management to deal with complaints by significantly reducing their number. The highest-ranked complaints from customers of the car industry in Iran are those related to delivery time, price alternations, customer service support and quality issues. Surveying the list of complaints shows that paying attention to the four most voiced complaints can reduce them more than 54%. Management can make appropriate strategies to improve the production quality as well as business processes, thus producing a significant number of customer complaints.

This paper proposes a comprehensive approach to critically analyse the VoCs by combining qualitative and decision-making approaches including K-mean, FCOPRAS, fuzzy Delphi and FBWM. This is the first paper that analyses the VoCs in the automotive sector in a developing country’s context involving large-scale decision-making problem-solving.

The idea to use computers for teaching and learning is over 50 years old. Numerous attempts to use computers for knowledge dissemination under a variety of names have failed in many cases, and have become successful in others. The essence of this paper can be summarized in two sentences. One, in some niches, applications tend to be successful. Second, attempts to fully eliminate humans from the educational process are bound to fail, yet if a large number of aspects is handled well, the role of teachers can indeed be much reduced. The paper aims to discuss these issues.

Report on experimental results.

In some niches, applications of e-Learning technology tend to be successful. However, attempts to fully eliminate humans from the educational process are bound to fail, yet if a large number of aspects is handled well, the role of teachers can indeed be much reduced.

A number of features that seemed essential in earlier e-Learning systems turn out to be superfluous.

New e-Learning systems have to concentrate on quality of content, not complex technology.

E-Learning the right way helps learners, teachers and institutions.

Experiments reported verify or do the opposite of often loosely stated opinions.