Towards a plurilingual habitus: engendering interlinguality in urban spaces

This article focuses on the potential of the multilingual city to create spaces in which monolingual hegemonies may be challenged, inclusive, intercultural values may be nurtured, and plurilingualism may be valorised. Following a contextualisation of linguistic diversity in theories of globalisation and superdiversity, discourses of deficit and power are addressed, arguing that the problematisation of multilingualism and pathologisation of plurilingualism reflect a monolingual habitus. Bringing about a shift towards a plurilingual habitus requires a Deep Approach, as it involves a critical revaluing of deep-seated dispositions. It suggests that the city offers spaces, which can engender interlinguality, a construct that includes interculturality, criticality and a commitment to creative and flexible use of other languages in shared, pluralistic spaces. It then proposes critical, participatory and ethnographic research in three multidimensional spaces: the urban school and a potential interlingual curriculum; networks, lobbying for inclusive policy and organising celebratory events in public spaces; and grass roots-level local spaces, some created by linguistic communities to exercise agency and maintain their languages and cultures, and some emerging as linguistically hybrid spaces for convivial encounter

An adaptive optimization strategy based on mixture of experts for wing aerodynamic design optimization

International audienceIn the field of aircraft design, the last few decades have focused on the iterative improve- ment of conventional tube-and-wing designs to reduce cost, noise, and emission. Never- theless, the growing expectation in terms of environment impact for the next generation of aircraft pushes for more radical changes in the design. For unconventional aircraft configurations, the need to integrate more accurate data coming from higher fidelity analysis earlier in the design process becomes more and more necessary. However, high-fidelity tools require long computation times and usually are associated with high-dimensional problems, both in terms of design variables and constraints. Therefore, these optimizations are often done at higher computational cost (gradient-based algorithms) in order to decrease the number of necessary function evaluations. In addition, the use of the adjoint method is often implemented to accurately and efficiently compute derivatives for large numbers of design variables. At the same time, new methods have been investigated to obtain opti- mized configurations at a reasonable computational cost. The work presented in this paper focuses on SEGOMOE algorithm, a solution to tackle this kind of optimization process of complex design problem through the use of an enrichment strategy approach based on mixture of experts surrogate models. Two aerodynamic shape optimization test cases, derived from cases developed by the Aerodynamic Design and Optimization Discussion Group (ADODG) are addressed: one with a single global minimum, and another one with several local minima. Both problems are nonlinearly constrained problems that involve a large number of design variables. Results are compared to gradient-based optimizers. A hybrid approach combining the advantages of both SEGOMOE and gradient-based optimization is proposed and evaluated to reduce the number of function evaluations and to ensure the convergence to the global optimum