For a long time, timber has taken the backseat to steel and concrete for largescale structures, but due to sustainability interests many developments have been made to improve its less desirable qualities. With the introduction of engineered wood products, large timber sections required for fire resistant design became economical and the timber structural behavior became more reliable. However, there are still many challenges when it comes to the seismic design of tall timber structures. Current modelling strategies are time-consuming to implement, provide inconsistent results, and do not account for the passive parameters which impact the seismic behavior of the structure throughout its lifetime. Since timber is a natural material, it is subject to varying levels of moisture content which impacts its stiffness. Furthermore, given the lightweightedness of timber structures (compared to concrete or steel alternatives), any changes to the mass distribution of the structure drastically changes its dynamic response.
This research project develops a computational workflow for the seismic analysis of tall timber structures which integrates the seismic analysis model seamlessly into the main design workflow, simplifies the process for setting the parameters in a semi component-level model for seismic analysis, includes a lifetime analysis option which considers the variables which impact the structural performance of the structure over time, and provides the engineer with component-level data over time. Python class objects are used to develop this computational workflow inside of the Grasshopper environment for Rhino, using the OpenSeesPy library for analysis. It follows the analysis standards provided by the (recent drafts of the) Eurocodes and supporting research papers. It has been developed to align with the most prominent tall timber construction types, as defined through the literature review. The analysis script utilizes the modelling strategy put forth by Rinaldi et al. (2021) to determine the effective stiffness of a cross-laminated timber wall, and its implementation was validated with a comparative analysis to the results of that research. The implementation of the full workflow and its impact on the design process is demonstrated through a case study, with results confirming the importance of including lifetime variables for analysis. This research increases the timeframe of analysis that the engineer can perform on tall timber structures such that the initial structural design can be informed by future predicted events, allowing for more resistant designs.

Balancing the requirements of urban planning with the need for rapid and efficient iterative design, while accurately assessing its detailed impact on existing surrounding buildings at a per-room level, presents a significant challenge in architecture design, the conversion and integration between multiple platforms introduce additional complexity, establishing high standards for designers to achieve. Integrating Building Information Modeling (BIM), Geographic Information Systems (GIS), and per-room daylight simulation into a unified workflow offers a promising solution. This thesis develops a web application that leverages Grasshopper(GH) scripts for backend processes, Rhino Compute as the intermediary API, andMapboxGL as the GIS-based front-end platform, enabling seamless user interaction with BIM data for customized daylight simulations.

Since the advent of digital tools, architects have sought ways to enhance and streamline the design process. Integrating these technologies bridges the gap between urban planning and indoor daylight simulation, facilitating real-time interaction and data manipulation. Grasshopper scripts are developed to compute Aperture-BasedDaylight Modeling (ABDM) metrics, Sunlight Beam Index (SBI), and sky lumen, providing a foundation for evaluating their relationships with traditional Daylight Modeling (CBDM) metrics like Daylight Autonomy (DA), Spatial Daylight Autonomy (sDA), and Useful Daylight Illuminance (UDI).

This research explores the potential of combining these advanced tools to create an interactive web application that allows users to manipulate building typology, location, scale,façade materials, and levels of detail (LOD) for surrounding city models. The study demonstrates a robust linear relationship between SBI and the daylight metrics DA, sDA, and UDI, with room geometry playing a crucial role. Skylumens, however, show limited effectiveness as a CBDM alternative.

The thesis concludes that MapboxGL is a promising platform for integrating BIM models into room-based daylight simulations, offering an intuitive user interface for urban planners and designers. Rhino Compute technology ensures smooth data transfer and interaction, significantly enhancing the workflow. The study results show that SBI has a linear relationship with traditional CBDM metrics. However, multiple moderating variables affect this relationship, and it does not apply to north-facing rooms. Thus, SBI is not a current substitute for traditional CBDM metrics. Overall, this thesis provides a comprehensive framework for integrating BIM, GIS, and daylight simulation into a cohesive system, paving the way for more efficient urban planning and design practices.

Exhibition 15 February – 1 March 2018, Faculty of Architecture (Delft University of Technology), Oostserre