Generative design using personas

Researchers: Vinu Subashini Rajus, Liam O’Brien, Gabriel Wainer

Inhabitants play a crucial role in the sustainable outcome of green buildings. Due to privacy, interactive behavior of occupants is not apparent to the designers. Inaccessibility to this information leads the designers, engineers to making assumptions of occupant behavior in building designs. Often, the predicted consumption tends to be significantly lower than actual usage. Nowadays, sensors and IoT enables designers to have information in buildings that may give knowledge on occupants’ interactive behavior. The goal is to identify typical interactive behavior (Personas) in buildings based on measured data and to evaluate building performance using the persona models for better sustainable outcomes.

DEVS Based GIS Optimization for Large Scale Modeling and Simulation of Urban Spaces

Researchers: Bruno St-Aubin, Gabriel Wainer

City Model
Methodology

Sustainable cities are complex systems. Designing an urban space requires a planner to consider an ever-expanding number of factors. Multi-modal transit systems, increasing population density, responsible water, and power management or air quality control are only a fraction of challenges that must be faced. Geographic Information Systems (GIS) are well-established tools used to tackle design and planning at a large urban scale. Discrete Event System Specification (DEVS) based modeling and simulation is a technique well suited to the virtual representation of the complex sub-systems that inhabit urban space. This research proposes the development of an automated DEVS based methodology aimed at assisting users in the design of GIS models of urban systems through a constraint-based optimization (Generative design) process. The generative design will allow users to generate multiple potential designs, simulate the target systems, and analyze their strengths and weaknesses. The evolution develops new and novel designs that build upon the previous iterations. The research aims at providing support for urban planners in designing spaces that optimally fulfill a set of constraints.

Generate and analyze the impact of the new buildings on the internal conditions of existing buildings.

Researchers: Nicolas Arellano Risopatron, Vinu Subashini Rajus, Arefeh Sadat Fathi and Anna Turrina

The School of Architecture at Carleton University has a new neighbor and, as in many other cases before in the history of university, the users of the existing buildings must contend with and adapt to new environmental conditions. The idea of this study is to propose ways to mitigate the negative impact of new buildings towards existing buildings on a university campus. The data collection consists of a qualitative survey given to students/users of the existing Architecture building and qualitative analysis of daylight and massing simulations. For this project, the use of Generative Design (GD) helped to analyze the data and to propose solutions to the current situation. Besides, the project will try to inform future Campus Master Plans in order to reduce possible negative externalities that new developments may produce towards adjacent existing buildings/spaces. This research focuses specifically on the relationship between the Architecture Building and the recently raised Nicol Building (Sprott School of Business) as a case study.

Sustainability Metrics for Generative Campus Design

Researchers: Cristina Ruiz-Martin , Vinu Subashini Rajus, Ala’a Al-Habashna, Hoda Khalil, Simon (Autodesk), Liam O’Brien, Stephen Fai, Gabriel Wainer

The goal of this project is to develop a collection of metrics that can be used independently or collectively to evaluate design proposals at a campus scale (working towards an urban scale). For example, flexibility metric (e.g. Olympic village or adaptive classrooms), qualitative / subjective parameters (e.g. human comfort), health factors (e.g. exposure over time), amenity locations: WiFi coverage / restrooms / study areas / quiet areas.