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

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.

Placing CO2 Sensors for Occupants Detection

Researchers: Hoda Khalil, Gabriel Wainer

Research proved that CO2 sensors are among the most accurate in detecting the presence of occupants. In addition, CO2 sensors are non-intrusive, require no motion or special action to detect the occupant’s presence based on CO2 levels, and do not have extra cost since they are installed as part of the building code in Ontario since 2014. However, CO2 sensors are highly sensitive to the configuration, and the relationship between CO2 levels and occupancy information is not always linear. It varies case by case. (e.g., what will the effect of HVAC do on measured CO2 levels?). This motivates us to research the relationship between the closed space configuration and CO2 based occupancy detection. The goal is to determine the best placement of CO2 sensors for the most accurate occupancy detection based on the characteristics of the occupied space (e.g., dimensions, vents locations, etc.). Besides, we aim to calculate the latency between the arrival/departure of an occupant and the detection of an increase/decrease in CO2 levels, respectively.
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A Robust Discrete Event Methodology for Modeling and Design of Reliable Cyber-Physical System

Researchers: Joseph Boi-Ukeme, Gabriel Wainer

Energy management and conservation in buildings are facilitated by the use of equipment that monitor changes to the environment and ensure that appliances are controlled accordingly. These equipments can achieve this by the use of sensors, actuators, and control systems. The design, development, and operation of sensors, actuators, and control systems are governed by the theory of Cyber-Physical Systems (CPS). Recent trends in CPS design have imposed the need for increased performance demands and complex usage, this has significantly changed the manner of interaction between the cyber and the physical components. They are now tightly coupled and integrated at every level, making it challenging to design cyber components separately from the physical components. In addition to design complexity, another very important issue to be considered is reliability.
The main goal of this work is to present a robust discrete event approach for the design of cyber-physical systems (CPS). This method is built on an existing methodology called Discrete Events Methodology for Embedded Systems (DEMES). Starting with DEMES, we implement certain changes to accommodate the complexity and tight inter-connectivity of the physical and cyber aspects of a CPS. The various aspects of the method considered for improvement include: the development of a formalism for real-time fault definition in cyber-physical systems at the design stage using DEVS; a method for real-time fault detection and diagnosis of CPS using the DEVS formalism; and the development of techniques to guarantee fault-tolerance in CPS.