Fiona Bénard

Digital transformation is increasingly reshaping sustainable building design by enhancing innovation, accuracy, and productivity through advanced digital tools. This study investigates how users’ self-reported familiarity with perceptions and use of modeling, simulation, and artificial intelligence (AI) applications contribute to sustainability-oriented design practices. A quantitative cross-sectional survey design was adopted, informed by a narrative review of the literature. The survey targeted students, academics, and recent graduates in architectural engineering. Quantitative data were analyzed using descriptive statistics, ranking analysis, and Multiple Factor Analysis (MFA) to examine digital competency patterns and tool evaluation criteria. The results reveal a common dimension of self-reported digital familiarity and proficiency across modeling, simulation, and AI applications, highlighting the importance of hybrid digital skillsets in sustainability-oriented workflows. Modeling, simulation, and AI applications collectively contribute to a unified competency dimension, highlighting the importance of hybrid digital skillsets. While traditional modeling tools demonstrate stable and widely shared perceptions regarding accuracy and productivity, AI-based tools exhibit more heterogeneous perceptions across functional categories. The second MFA dimension was more strongly associated with modeling than with simulation or AI, without establishing distinct specialization pathways. This study emphasizes the need for integrated digital workflows and competency-based education to support sustainable design. It contributes empirical evidence to the understanding of digital transformation in architectural practice and highlights emerging challenges and opportunities associated with AI integration.

In the context of resource depletion and global warming, the energy transition has become a necessity. To provide a basis for analysis and to support countries in this transition, it is necessary to better understand this transition. The creation of a good measurement tool could help. This paper proposes a measure of national resilience through an analogy to kinetic energy. Preliminary results show that some countries have strong potential for resilience in the energy transition. Inequalities exist and still exist in terms of accessibility to energy but the energy transition could generate an interesting catch-up for the most vulnerable countries. Finally, the impulse of the transition seems to be easier than the completion of this transition.

Succeeding energy transition is the current challenging objective of many remote islands such as Reunion Island to reduce their dependency to fossil resources. To define an efficient energy framework strategy for the territory, it is important to be able to assess the electricity consumption intensity per typology of consumers. A particular attention must be paid on building electricity consumption in energy planning scenarios. This paper proposes to investigate the electricity consumption ratio per square meter per building type which appears as a relevant indicator. The proposed methodology aims at filling the lack of data (ratio kWh/m2/ type of consumers) when this information doesn’t exist for a territory. This type of ratio can be useful in two ways: on the one hand to characterize the building energy demand, and, on the other hand, to understand the consumption mode of the inhabitants. We can therefore provide future energy policy framework in favor of demand-side management what is a key step, a lock to solve for the deployment of sustainable cities. This work calculates electricity consumption ratios per area by using a GIS (Geographic Information System) method, distinguishing the type of building. The case of Reunion Island is studied and four building categories are identified corresponding to the functional characteristics such as industry, administration, companies and residential. The results highlight that residential sector has one of the lowest electricity ratios with a value of 29.84 kWh/m2, but also the highest part of electricity consumption, 45.2%. The different ratio value has been cross validated by estimating municipalities electricity consumption based on the distribution of consumers and the associated ratio.