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This paper proposes to extend the combination of Extended Finite Element Method (XFEM) and Level Set Method (LSM) from structural mechanics to electromagnetics. Based on this approach, the actual stage of the research work, dedicated to the investigation, development, implementation and validation of a shape optimization methodology, particularly tailored for 2D electric structures is described.

The proposed numerical approach is based on the efficiency of the XFEM and the flexibility of the LSM, to handle moving material interfaces without remeshing the whole studied domain at each optimization step.

This approach eliminates the conventional use of discrete finite elements and provides efficient, stable, accurate and faster computation schemes in comparison with other methods.

This research is limited to shape optimization of two‐dimensional electric structures, however, the work can be extended to 3D ones too.

The implementation of the proposed numerical approach for the shape optimization of a planar resistor is hereby described.

The main value of the proposed approach is a powerful and robust numerical shape optimization algorithm that demonstrates outstanding suppleness of handling topological changes, fidelity of boundary representation and a high degree of automation in comparison with other methods.

This study aims to examine travel patterns and factors that explain children’s use of green space for outdoor learning. This knowledge will be valuable for urban planners and policymakers to plan, design, develop and maintain green spaces that consider children’s interests.

The analysis consists of three steps. First, this paper performed a mapping analysis to explain the accessibility and services of green spaces in supporting children’s education. Second, using data from a survey distributed to school teachers, this paper explored factors affecting trip frequency, travel distance and walking when visiting green spaces. Third, this paper interviewed teachers and conducted observations and conversations with children to gain additional insights.

The quantitative analyses found that size, path network linkages, path length, use for nature observation, play features, path density, walking and biking may influence children’s preference for using green spaces. This study identified five factors (playing, socialising, exploring, biodiversity and accessibility) that drive children to visit green spaces.

There is limited knowledge of the links between green space and children’s travel patterns and factors explaining the use of green spaces. To the ebst of the authors’ knowledge, this study seems to be the first attempt to introduce a mix of methods containing mapping, qualitative and quantitative analyses to explain children’s use towards green spaces.