Sie sind hier: Startseite Kolloquium Climate Resilient Habitats: On Digital Modeling and Simulation Capabilities Capturing Spatial Variations in Local Environments

Climate Resilient Habitats: On Digital Modeling and Simulation Capabilities Capturing Spatial Variations in Local Environments

Prof. Dr. Dominik L. Michels, Professor of Computer Science holding the professorship of Intelligent Algorithms in Modeling and Simulation (IAMS) at the Technical University of Darmstadt

Art des Termins
    Wann 06.04.2023
    von 13:30 bis 14:30
    Wo b-it, room 0.107, Friedrich-Hirzebruch-Allee 6, 53115 Bonn
    Termin übernehmen vCal

    Climate change impacts communities and human habitats worldwide and locally in different ways. A multitude of interdependencies between, for example, geophysical and human-made factors make adaptations to this changing world extraordinarily challenging. Coarse prediction models, for example predicting an increase of temperature and a decrease of rainfall in specific regions, are not sufficient to allow communities to prepare for and adapt to the multifaceted impacts in their local environment. Urban planning, for example, in progressively heat-stricken areas should incorporate building surfaces that reflect radiation, allow cooling wind to flow freely through neighborhoods, and strategically place plants in areas where shade is needed most. In order to address such needs, we aim to develop the required digital modeling and simulation capabilities by combining our expertise in geometric modeling and computational architecture, physics-based modeling and numerical simulation, and visualization. The necessity for these capabilities is similarly evident if we consider rural and farming regions or forests; these complex ecosystems also maintain their own climate.

    Similarly, detailed geometric models are required as it has recently been established that climate change not only has an impact on plant ecosystems, but that vegetation also contributes to local weather variations, resulting in diverse microclimates in contrast tothe overall macroclimate. On a larger scale, urban, rural and farming, and forest areas are interconnected and changes within each area can easily cause effects beyond the direct environment. In this context, modeling and simulation of weather phenomena is at the core of our work considering detailed representations of the underlying geometric structures at the level of individual objects such as buildings or trees. Such high-resolution data are of fundamental importance in order to adapt to the associated challenges of a changing environment and to support a climate-resilient community. Furthermore, the data obtained from modeling and simulating these complex environments could serve as synthetic training data, leveraging machine learning capabilities for smart cities and the development of state-of-the-art land use concepts.

    The talk is part of the lecture series "Innovation Pathways to Sustainability" by the TRA "Innovation and Technology for Sustainable Futures".

    Please note that a short registration is mandatory to attend in person: