Urban Energy + Thermal Comfort Design Software Development

Urban heat island effect [UHI] is known to affect outdoor thermal comfort, human health, as well as heating and cooling loads for buildings. Yet urban planners, designers and their consultants currently lack tools or methods to deliberately incorporate this effect into the design of new or renovated neighborhoods.

Urban weather generator [UWG] is a new simulation tool that is the first of its kind to incorporate UHI in energy simulations and allow designers to articulate their architectural designs with microclimatic considerations. It suggests improvements on building geometries and materials to improve thermal comfort and energy efficiencies. The software enables urban designers to parametrically test built densities and vegetation for masterplanning. Urban planners can advocate zoning regulations such as building height and land use as well as policies for traffic intensity and cool roof with energy and thermal implications of these interventions. As UHI is directly affected by how buildings are clustered together in a city and accelerated with the current trend in urban population growth, my goal is to facilitate early adoption of sustainable engineering design concepts in the design process and policy development.

I developed two versions of the software: the stand-alone and the plug-in for 3D modeling software Rhinoceros. The user interface is simplified with reduced number of user inputs via sensitivity analysis. Users are able to run multiple simulations at once and compare the results using thermal comfort and energy metrics. The tool is developed with feedbacks from urban design and planning practitioners as well as energy consultants to create a useful and usable tool towards a fully integrated climate-based design in architecture.

The tool has been developed in C# and is available for download free of charge on the research website .

MS Thesis | 2013 - 2015
MIT
Advisors: Leslie Norford, Christoph Reinhart
Undergraduate research assistants: Lingfu Zhang, Bokil T Lopez-Pineda

Programming LanguagesC#, Matlab

Awards Third Prize, MIT Center for Environmental Sensing and Modeling workshop [2014]

Publications 14th International Conference of the International Building Performance Simulation Association [Paper and presentation, 2015]
Ninth International Conference on Urban Climate [Presentation and proceedings, 2015]

Urban Weather Generator Workflow

In a recent survey of energy modelers and architects by Samuelson et al. (2012) [1], 23 out of 62 participants [37%] answered that the results of energy simulations “rarely” or “occasionally” had impact on design decisions even in AEC [Architecture, Engineering, and Construction] firms which employ in-house energy modelers. This is a direct result of this delayed use of tools within the design process, and therefore it is crucial that we create a tool within the designers’ current design platform to encourage early integrations of energy and thermal comfort concepts with massing design.

Using UWG, the urban designer can iteratively improve their design for thermal comfort and energy consumption within Rhino.

Making The Research Software Usable for Designers

UWG's engine was developed by the predecessor of this project Bueno [2012] [2] and is a building energy model based on Town Energy Balance scheme and energy balances applied to control volumes in the urban canopy and boundary layers. It estimates the hourly urban canopy air temperature and humidity using weather data from a rural weather station.

As this research model requires over 50 inputs, sensitivity analyses were conducted for Boston, MA and Singapore, Singapore to reduce the number of required input parameters. The commonality of results allowed us to decrease the number of inputs by over 46% [below left] and thus increase the speed at which the users can evaluate their designs for thermal comfort and energy usage. The key parameters [below right] are site coverage ratio, façade-to-site ratio, and sensible anthropogenic heat, which are designed during the master planning phase of the urban design process. All of the parameters that have small influence on the UHI are moved to the advanced setting.

In the Rhino version, urban geometry parameters [above right] is automatically calculated from the 3D model, leaving building construction materials, land usage, and non-building sensible heat [i.e. traffic] as required inputs.

GUI User Experience

As this is the first design tool for UHI modeling, the initial interface design is based on the existing and widely used interfaces [i.e. DesignBuilder and umi] so that users can easily familiarize themselves with the environment. The program was tested with seven urban design practitioners and novice users who have not used design simulation tools before as well as five energy consultants who have previously used other environmental performance simulation tools.

The hierarchy of the building materials information has been redesigned to resemble the existing tools. The summary section shows the assembly of the selected item.
The results viewer helps users to compare simulation results to select an effective design strategy for the next round of simulations.

The user interface is organized by the users’ goals. The output from each functions or already existing files can be used to run another successive feature of the GUI.

Tool Validation: Kendall Square Development

The workflow is demonstrated through a case study of the new 130 thousand square meter development on the MIT East Campus in Cambridge, MA, USA.

We propose the below alternative [Alt 6] to MIT's plan for a more thermally comfortable and energy-efficient development.

An IPCC-based climate change prediction is considered along with UHI to evaluate the outdoor comfort. The average contribution of UHI is about a tenth of the climate change. The urban cooling in 2020 is most likely from the increase in open space [i.e. the urban canyon is wider and less heat is trapped]. In other words, the climate change is mitigated via a local change in the site morphology.

*responsive & user-friendly documentation of the urban microclimate research

References
[1] Samuelson, H., Lantz, A., Reinhart, C. F. (2012) Non-technical barriers to energy model sharing and reuse. Building and Environment, 54, 71-76
[2] Bueno, B., Norford, L., Hidalgo, J., Pigeon, G. (2012a). The urban weather generator. Journal of Building Performance Simulation 6(4):269–81