Program
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Invited Talks
Embracing Daylighting Dynamics in Human-driven Design
Marilyne Andersen – Ecole Polytechnique Fédérale de Lausanne (EPFL)
This talk will explore current research efforts at the interface between architecture and building technology, with a focus on the integration of daylighting performance in design through simulation methods. The impact of natural lighting contributions on occupants’ well-being, notably from their health and biological clock perspective, but also through perceived visual and thermal comfort or from an emotional response standpoint, in order to bring these considerations to become integral components of design support, providing guidance towards places of delightful – and daylightful – living.
Presenter Biography
Marilyne Andersen has a background in physics and works at the interface between architecture and engineering. Her research and consulting activities focus on building performance in the architectural context in general, and the use and optimization of daylight in buildings in particular. She has a PhD in Building Physics from EPFL, was a scholar at the Lawrence Berkeley Lab as well as tenure-track Professor at MIT before joining EPFL as faculty member. She is a Full Professor at EPFL and Dean of the School of Architecture, Civil and Environmental Engineering, Head of the LIPID Lab, and co-founder of the consulting spin-off OCULIGHT dynamics.
Marilyne Andersen’s research field situates itself at the interface between architecture and building technology, and focuses on the integration of building performance in design, with an emphasis on daylighting and passive solar strategies. From an initial focus on video-based goniophotometry and complex window materials, she broadened her research interests to architectural design and to its bridging opportunities with photobiology and neuroscience, psychophysics, computer science and other fields traditionally remote from building technology. She works on a wide range of subjects, including visual and thermal comfort, tools for early stage design, circadian photoreception and health, and advanced facade technologies for daylight redistribution. She is the author of over 100 refereed scientific papers, recipient of several awards including the prestigious Daylight Research Award 2016, and is a member of the Board of the LafargeHolcim Foundation for Sustainable Construction. She was the leader and faculty advisor of the Swiss Team and its NeighborHub project, who won the U.S. Solar Decathlon 2017 competition.
The Fusion of Design and Performance: Integrating Building Science into Architectural Practice
Andrea Love – Payette
The lecture will focus on an organizational case study on the integration building science into its design process. The talk will show how the integration of building simulation into the design process has been leveraged to inform and drive architectural design, transforming our firm culture and building an energy literacy within the organization.
Presenter Biography
Andrea is the Director of Building Science and Principal at Payette, an architecture firm in Boston, working across all projects to bring rigor to the performance of their work. Additionally, she leads the firm’s internal research projects, and was the Principal Investigator on the AIA Upjohn Grant focused on thermal bridging. She has also been a Lecturer at MIT and at Harvard where she teaches a class on building performance. Andrea is a licensed architect with her BArch from Carnegie Mellon as well as a Masters in Building Technology from MIT where she was the recipient of the Tucker-Voss Award. She is a LEED Fellow and was a 2017 recipient of the AIA Young Architect Award.
Andrea joined Payette in 2011 to start the Building Science group which leads internal research projects and sustainability efforts for the firm. The group works across all projects in the office providing integrated, iterative performance modeling during design to enable project teams to make informed design decisions. She particularly focuses on early in the design process when there is the greatest opportunity to influenced design. Much of Andrea’s research has focused on building envelopes and exploring how they impact energy usage, occupant comfort, and mechanical systems. A licensed architect who also has a degree in building performance, Andrea seeks to marry performance and design in order to achieve beautiful, high performing buildings.
Research Matter(s)… Architecture, Engineering, and Technology
David Gerber – Arup and University of Southern California (USC)
In "Research Matter(s)" Dr. Gerber will speak about research at Arup and the drivers that influence the design and engineering research directions of travel. Included in this description is a reflection upon technological trends and their influence upon designing for and with complexity. His talk includes examples from both industry and the academy and purposefully raises questions about our plausible futures and highlight the essentialism of design exploration in the fourth industrial revolution.
Presenter Biography
Dr. Gerber is Arups’ Global Research Manager. David holds a joint appointment at USC’s Viterbi School of Engineering and the USC School of Architecture as an Associate Professor of Civil and Environmental Engineering Practice and of Architecture. Dr. Gerber is also the program Director for the Civil Engineering Building Science undergraduate program and teaches in both the Viterbi School of Engineering and the School of architecture. David Gerber received his undergraduate architectural education at the University of California Berkeley (Bachelor of Arts in Architecture, 1996). He completed his first professional degree at the Design Research Laboratory of the Architectural Association in London (Master of Architecture, 2000), his post professional research degree (Master of Design Studies, 2003) and his Doctoral studies (Doctor of Design, June 2007) at the Harvard University Graduate School of Design.
Dr. Gerber’s work is focussed on developing a richer synthesis of Architecture with computing, engineering and related sciences for the design and engineering of the built environment. At the core of his interest is the discovery of systems, tools, and new knowledge for architecture, and urban design. His professional experience includes working in architectural, engineering and technology practices in the United States, Europe, India and Asia for Zaha Hadid Architects in London, England; for Gehry Technologies in Los Angeles; for Moshe Safdie Architects in Massachusetts; The Steinberg Group Architects in California; and for Arup as the Global Research Manager. Dr. Gerber’s research has been industry, fellowship, and NSF funded and is focussed on the development of innovative systems, tools, methods for design of the built environment. He currently advises, and co advises PhD students from Architecture and Engineering on topics that integrate computer science, robotics, and engineering, with architecture.
Paper Abstracts
Machine learning algorithm-based tool and digital framework for substituting daylight simulations in early- stage architectural design evaluation
Kacper Radziszewski, Marta Waczyńska
The aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less time-consuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have been used to verify the reliability of applying the latter into an early stage architectural design process. The framework was based on the computationally generated data sets build on various office models variants followed by daylight simulations. In order to predict the simulations values based on the given office parameters with artificial neural networks algorithm, a specific tool was designed as an alternative to computer simulations. The designed tool and simulations results were compared against computing time and values differences. The above findings of the research proof the reliability of the new methods as a tool during an early-stage architectural design process likewise conventional daylight simulations.
Artificial Neural Network-Based Modelling for Daylight Evaluations
Clara-Larissa Lorenz, Michael Packianather, A. Benjamin Spaeth and Clarice Bleil De Souza
The climate based Daylight Autonomy (DA) metric has been gaining ground in the field of sustainable building design as a measure for the amount of daylight within spaces and associated energy savings. In this study, Artificial Neural Networks (ANNs) were used to predict DA levels in interior spaces as an alternative to computationally expensive simulations. Research was carried out in three phases of increasing complexity: First, a neural network was trained and validated for a single design space. Subsequently, the window design was altered and a neural network was trained and tested on its ability to predict DA levels according to changes in window design. Lastly, the neural network was trained to account for the effects of shading from an external obstruction. After sufficient training, the ANN, during the recall stage, was able to predict DA, on average, within 3 DA short of the simulated DA results for both the shaded and unobstructed scenario. The results obtained show the potential of neural networks as a prediction tool for estimating Daylight Autonomy.
OCUVIS: A Web-Based Visualizer for Simulated Daylight Performance
Siobhan Rockcastle, María L. Ámundadóttir and Marilyne Andersen
This paper introduces an interactive web-based visualizer for multi-metric daylight simulation results, named OCUVIS. It is able to display simulation-based results for a diverse range of ocular human-centric metrics such as non-visual health potential (nvRD), daylight-related visual interest (mSC5) and visual comfort (DGP with Ev), as well as horizontal illumination metrics such as spatial Daylight Autonomy (sDA), Annual Sunlight Exposure (ASE) and Daylight Factor (DF)). To provide a holistic representation of performance across a multi-directional field-of-view, OCUVIS creates an interactive visualization of results over time and across space, linking temporal and 3D graphics. This allows the user to explore the impacts of dynamic sky conditions, view position, view direction and program use on localized and building scale performance. OCUVIS bridges the gap between human and building-scale daylight potential to offer a more holistic and intuitive representation of daylight performance in buildings.
Assessing the Circadian Potential of an Office Building in the Southeastern US
Armin Amirazar, Mona Azarbayjani, Ok-Kyun Im, Amir Hosseinzadeh Zarrabi, Roshanak Ashrafi, Robert Cox, and Austin Johnson
Circadian rhythm alludes to the processes of the human body needed for a person to function healthily and properly in his daily life. It also refers to the internal clock that resets primitively with the rise and set of the sun. Studies of circadian rhythm prioritize the needs of users within a space and reintroduces the crucial value of designing for the occupants experience, well-being, and comfort. In this study, effective circadian stimuli that office workers receive are evaluated to address the sufficiency of daylighting conditions in an actual office building. Climate-based daylight modeling was used to capture an hourly vertical illuminance in a model office space at the eye level within two different time periods across 12 view directions. Results indicate that effective stimuli are present for more than 80% of the total office area for at least 71% of the week (5 of 7 days) during a year. Results can be used to visually examine different building zones (perimeter vs interior) in terms of availability of circadian effective stimuli over the specific window of time. The evidence from this study can assist designers to better understand biological effect of light exposure on occupants health and well-being during the design phase of the project or to examine existing spaces.
Predicting Duration of Daylight Exposure for Caregivers Using Discrete Event Simulation and Climate-Based Daylight Modeling (Short Paper)
Khatereh Hadi, Olivia Pewzer
Exposure to daylight can significantly improves caregivers’ wellness and performance in healthcare settings. Research on caregivers has shown that duration of exposure to daylight was one of the main predictors of work-related strain and burnout, which can compromise both caregivers’ performance and patient safety. This paper highlights implications of discrete event simulation and climate-based daylight modeling in developing a framework for predicting the duration of daylight exposure for caregivers, considering their work processes and space occupancy patterns in healthcare settings.
Addressing Pathways to Energy Modelling through non-manifold Topology
Aikaterini Chatzivasileiadi, Simon Lannon, Wassim Jabi, Nicholas Mario Wardhana and Robert Aish
This paper presents a comparison of different pathways for the energy modelling of complex building geometry. We have identified three key modelling questions: first, how can the spatial organisation of the building be appropriately represented for energy analysis? Second, how can curved building geometry be post-rationalized as planar elements given the planar constraints associated with energy simulation tools? And third, how can an exploratory design process be supported using a "top-down" rather than a "bottom-up" modelling approach? Using a standard office building test case and EnergyPlus, the following three pathways were explored: (a) OpenStudio using a non-manifold topology (NMT) system based on an open-source geometry library, (b) OpenStudio using the SketchUp 3D modelling tool and (c) through the DesignBuilder graphical interface. The efficacy of the software used in these pathways in addressing the three modelling questions was evaluated. The comparison of the pathways’ capabilities has led to the evaluation of the efficacy of NMT compared to other existing approaches. It is concluded that NMT positively addresses the three key modelling issues.
Case Study for the Application of Multidisciplinary Computational Design Assessment and Constructability Optimisation Tools
Alexandros Christodoulou, Mathew Vola, Gijs Rikken
Building designs have to meet multiple engineering and financial requirements. This makes the development of complex architectural forms challenging. Computational automation can largely facilitate the realisation of such forms, through the reduction of time needed for design checking and optimisation. This is demonstrated through the case study of a 3-tower design, called Valley, currently under construction in Amsterdam, NL. The development of a computational tool enabled the design team to automatically check that the daylight (sun hours and daylight factor), structural (cantilever span) and other performance criteria (solar load, view privacy, apartment floor area and terrace floor area), as well as applicable daylight code requirements, were met in all the rooms of the design. The tool provided almost direct feedback to the design team, allowing them to reshape and check the model multiple times, leading to the continuous iterative improvement of the design. The use of parametric design tools also resulted in reduced construction costs, through a geometric optimisation that largely reduced required formworks. Finally, the parameterization of the design allowed the design team to demonstrate the design’s increased performance to the client, through comparisons against random variations similar to the design and against rectilinear tower designs.
Parametric Modeling Framework for Architectural Integration of BIPV Systems
Linus Walker, Stefan Caranovic, Johannes Hofer, Illias Hischier, Amr Elesawy, Arno Schlüter
Technical advances enable new design possibilities for building integrated photovoltaics (BIPV) with improved aesthetics and energy performance. Every BIPV project is unique and requires high effort in terms of design and technical planning. In this work, a workflow for a conceptual parametric BIPV planning tool is proposed. The tool helps designers to take informed decisions and accelerates the planning process. Furthermore, it enables new approaches for module and electrical layout optimization. The main steps of the framework involve a parametric system definition, followed by an automated module placement, an irradiance simulation and an electrical performance calculation. The used software include Rhino/Grasshopper, Ladybug, Daysim and Python. For the early design stage an appropriate trade-off between accuracy and speed should be made for fast simulations with fast feedback while detailed and calculation intensive simulations can be used for optimization in the intermediate design sate.
Methodology for Determining Fenestration Ranges for Daylight and Energy Efficiency in Estonia
Francesco De Luca, Timur Dogan and Jarek Kurnitski
Daylight is of interest in architecture for two reasons: On one hand it is appreciated and requested to make the interiors of buildings pleasant and comfortable and to save energy for electric lighting and heating. On the other hand excessive direct solar exposure can cause occupant discomfort and harm the energy efficiency of buildings causing overheating during the warm season. In Estonia, a daylight ordinance establishes the minimum average Daylight Factor for residential buildings and an energy efficiency ordinance sets the maximum acceptable degree hours of overheating. The two requirements are potentially conflicting. The recent architectural trend in Estonia is to use very large windows in residential building design. Even in the Estonian heating dominated climate this causes overheating issues that lead to the previously mentioned regulations. This paper explores the relationship of opening ratios, daylighting and overheating potential analyzing 7812 design variants taking into account room, windows and external wall sizes, presence of shading or balconies and different types of ventilation. It is shown that the overheating potential can be contained and both requirements can be satisfied only using measures such as shading and ventilation.
FloorspaceJS—A New, Open-Source, Web-Based 2D Geometry Editor for Building Energy Modeling (BEM)
Daniel Macumber, Scott Horowitz, Marjorie Schott, Katie Noland, Brian Schiller
Many industries are rapidly adopting web applications that are inherently cross platform, mobile, and easy to distribute. The Building Energy Modeling (BEM) community is beginning to pick up on this larger trend, with a small but growing number of BEM applications starting on or moving to the web. Currently, there are a limited number of open-source libraries or frameworks specifically tailored for BEM web applications. This paper presents FloorspaceJS, a new, open-source, web-based geometry editor for BEM. FloorspaceJS operates on a custom JSON file format, is written completely in JavaScript, and is designed to be integrated into a variety of applications, both web and desktop applications. FloorspaceJS allows users to define building geometry story-by-story with custom 2D floor plans appropriate for many BEM use cases.
Coupled Modeling and Monitoring of Phase Change Phenomena in Architectural Practice
Billie Faircloth, Ryan Welch, Yuliya Sinke, Martin Tamke, Paul Nicholas, Phil Ayres, Mette Ramsgaard Thomsen, Erica Eherenbard
Geometries designed with carefully controlled heat absorption and heat transfer profiles often elude designers because of the complexity of thermodynamic phenomena and their associated discipline-specific numerical models. This project examines the behavior and design of geometries associated with non-isolated thermodynamic systems by constructing a material prototype that is fully coupled to a mechanistic modeling interface. The prototype, a facade system of phase change materials, was mounted on an adjustable outdoor testbed. Its baseline geometry was continuously monitored over two seasons and characterized with respect to variation in liquid and solid states. The mechanistic model, which uses a finite element method, incorporates multiple components including geometry, orientation, material properties, context geometry (e.g. buildings and vegetation), weather, climate, and an array of sensors monitoring the real-time temperature distribution of the testbed and phase-change materials. Data were continuously collected from the testbed and used to calibrate, validate, and verify the mechanistic model. In turn, the calibrated mechanistic model provided a platform for the design of new facade geometries and predictions of their behavior. The project demonstrates an integrative modeling approach, orchestrating handshakes and feedback loops between disparate spatial and temporal domains, with the ambition of defining a cogent design framework for practices that are trans-scalar, trans-temporal, and trans-disciplinary.
Multivalent Analysis of Double-Skin Envelope Dynamic Hygrothermal Louver System
Aletheia Ida
This research introduces a novel lyophilized hydrogel for double-skin envelope (DSE) integration as a dynamic louver system to provide dehumidification of moisture, daylighting modulation, and recuperation of water condensate. The work links empirical experiments for thermal, optical, and sorption properties of the hygrothermal materials alongside system scale analytical models to inform energy and water conservation measures. The system scale analyses are conducted with LBNL WINDOW7 in combination with numerical analytical models, in addition to select computational fluid dynamic (CFD) studies for development of louver geometries to optimize sorption effectiveness in the DSE cavity airstream. Effective heat transfer and visible transmittance values for the dynamic states of the DSE hygrothermal louver system are then linked to building scale analyses in the Rhino-Grasshopper platform using the Honeybee plug-in to run EnergyPlus. The dynamic state envelope system is assessed through annual integration modeling for hothumid climate conditions. The work introduces new aspects in simulation modeling with integration of the standard mechanical air-handling system functions to be coupled with multi-state dynamic properties for the envelope system in building scale analyses. A sorption coefficient is identified for analytical modeling of the DSE hygrothermal louver cavity thermodynamics. The work also integrates a new calculation tool in the simulation platform for evaluating potential water recuperation from humidity sorption and condensate release functions.
Adaptive Roof Aperture for Multiple Cooling Conditions
Dorit Aviv
We develop a kinetic cooling roof device for desert climate, which operates in multiple constellations triggered by sensor input. The device is designed for a dual response: as a wind catcher it captures external airflow and channels it into the buildings interior volume by orienting the roof opening toward the current prevalent wind direction. At the same time, the aperture is responsive to radiation – either avoiding direct solar radiation during the day or maximizing radiant cooling during the night by exposing the building’s interior to the night sky. To achieve these various states, the geometry of the design is simplified into a segmented cylinder with multiple blades that allow for myriad potential constellations to occur. A motorized joint with three degrees of freedom controls the position of each of the aperture’s blades. The range of possible outcomes and functional relationships in the system is tested with both digital simulations and physical prototypes. A wind tunnel test was conducted to compare the performance of different configurations.
Graphene Embedded Composites for Thermal Performance Optimization of Traditional Construction Materials (Short Paper)
Athanasios Zervos, Gelder Van Limburg Stirum, Ricardo Mayor Luque, Javier Lopez Alascio, Areti Markopoulou, Angelos Chronis, Alexandre Dubor, Giovanni Perotto and Athanassia Athanassiou
Although graphene is considered the material of the future, its research and applications have not yet reached the construction industry. This paper focuses on the potential of developing graphene-embedded composites to enhance the electrical and thermal performance of traditional and widespread construction materials such as concrete and clay. A number of performing prototypes were fabricated at different stages of the study using different approaches for embedding graphene nanoplatelets into clay and mortar. Our experimentation with these composites has led to the conclusion that there is significant potential in enhancing the thermal and electrical properties of traditional materials. These first tests demonstrate both the achievable performance as well as the feasibility of producing such composites without access to a professional grade laboratory.
The Centrality of the User
Gabriel Weiner, Billie Faircloth, Jon Sargent, Marilyne Andersen, Andrea Love
The panel is intended to provoke discussion on the role of the end user (building occupant) in performance assessments and building simulation. As we collect increasingly complex data about user behavior, preferences, and needs, how can and should simulation integrate the end user into predictions of performance and ultimately provide better support for design development/building operation. How user behavior/preferences/needs are being integrated into simulation? What are the current limitations/obstacles and emerging potentials/directions? How user data could/should/should not be integrated into simulation and the opportunity space that emerges from user-oriented workflows?
Simulating Thermal Comfort Analytically through Exergy Analysis
Hongshan Guo, Forrest Meggers
Modeling thermal comfort analytically is difficult, and becomes even harder to interpret when conventional numerical simulation tools use in-house assumptions within their algorithms to produce results with Fanger’s PMV/PPD models. In this paper, we propose to evaluate the human thermal comfort with exergy analysis as an alternative to the PMV/PPD model. Starting from reviewing prominent researches within the area, the paper shows the comparison between three welldeveloped human body exergy consumption models, in particular their underlying assumptions to evaluate their capabilities in evaluating the thermal comfort. Comparing existing literatures from the three research hubs and making sure the underlying assumptions are consistent, we believe in between the three models lies the future of an expanded landscape for exergy analysis not at single component or system efficiencies, but their combined capabilities to deliver thermal comfort.
Investigating the Link between CO2 Concentration,Thermal Comfort and Occupant Perception in Educational Buildings
Merve Kuru, Gulben Calis
Thermal comfort conditions, as well as CO2 concentration in educational buildings, indirectly affect students’ attention, comprehension and learning performance. Although the standards recommend thresholds for both thermal comfort conditions and CO2 concentrations in indoor environments, the perception of students might also affect their performance. This study aims at understanding the relationship between students’ perception towards existing conditions and actual measurements. A university building, which is located in the Mediterranean climatic region of Turkey, was selected as a test site. CO2 concentration, indoor air temperature, mean radiant temperature, relative humidity and air velocity were monitored for ten days in the heating season. In addition, a survey study was conducted to understand the perception of occupants. Predicted Mean Votes (PMV) were calculated to assess the thermal comfort conditions of the classroom whereas CO2 concentrations were evaluated according to ASHRAE Standard 62.1-2016. The correlation between PMV values and CO2 concentrations were analyzed via Pearson correlation coefficient. Moreover, the effects of occupants’ thermal sensation, relative humidity and air velocity perceptions on the CO2 perception were analyzed via cross-tabulation and chi-square independence tests. The main results show that: (1) 53% of measurements exceed the recommended target value of 1000 ppm by ASHRAE, (2) there is a strong positive correlation between PMV values and CO2 concentration, (3) CO2 perception of occupants are influenced by thermal sensation as well as relative humidity and air velocity perceptions.
Demand-controlled Ventilation through a Decentralized Mechanical Ventilation Unit for Office Buildings
Bonato Paolo, D’Antoni Matteo and Fedrizzi Roberto
The paper focuses on the energetic and economic profitability of demand-controlled ventilation (DCV) strategies implemented in a decentralized ventilation application for tertiary office buildings.DCV consents to modulate the ventilation rate over time and meet the ventilation demand of the zone minimizing the energy-penalty of overventilation. Its cost-effectiveness is however not always guaranteed, since it depends on buildings use, climate, HVAC features and it should be assessed for each application [1].Numerical simulations are carried out for a set of representative European climates to compare the effectiveness of three sensor-based demand-controlled ventilation strategies with a baseline control strategy. To this end, numerical models of the reference zone and the ventilation unit are developed in TRNSYS and the occupancy profile is defined with a stochastic approach to provide a more realistic user behavior.It is found that the energy savings (heating, cooling and fan energy consumption) achieved with sensor-based demand-controlled ventilation are very limited for the selected application in all scenarios. Energy efficiency measures – such as the use of a high-efficiency heat recovery unit, the exploitation of free cooling or the installation of an high-performance ventilation unit – can significantly limit the energy savings achieved with DCV.
Light Weight Look Ahead Options of Personal Interaction in Buildings
Vinu Subashini Rajus, Robert Woodbury
How do people interact with buildings? A building is a system, with many components that can affect energy use and thermal comfort. Designers and engineers using energy simulation typically assume inhabitants’ interaction to be fixed, scheduled or rule-based, as opposed to being active. They are constrained in their design deliberations by lack of knowledge and models of how people use buildings. On the other hand, inhabitants do not comprehend the effects of their interactions with building systems and elements about comfort and energy usage, because data on both usage and control is not visible, and effects are time-delayed. Inhabitants experiencing discomfort have multiple options from which to choose but have insufficient information on the effect of these options on energy usage and comfort. Light Weight Look Ahead Options (LWLA) focuses on the impact of personal choices on comfort and energy usage in buildings. LWLA predicts the energy usage and comfort levels in the building due to inhabitants interaction and compares it with the existing building conditions. LWLA is novel in its approach as it provides the inhabitants with possible actions and their effect on energy usage and comfort in the buildings. A user study reveals that LWLA helps the inhabitants’ to learn, negotiate, weigh choices (make decisions) towards more sustainable interactions.
To Participate or not to Participate? Selecting the Right Participant Profile for Thermal and Visual Comfort Studies
Gulben Calis, Merve Kuru, Jessica Mouawad
Energy consumption reduction in buildings poses great challenges to modern societies in which maintaining thermal and visual comfort is occupants’ primary desire in indoor environments. In order to determine satisfaction levels of occupants, surveys are widely used to obtain feedback with respect to thermal and visual perceptions. However, low participation to the surveys might cause misleading results, and, thus, result in defining wrong strategies to maintain occupant comfort in buildings. Therefore, factors that affect participation to the surveys have to be analyzed so that the surveys can be distributed to the most responsive profile. This study aims at investigating the relationship between factors related to participant profile (gender, age group, energy awareness level and the number of energy activities attended) and survey participation ratio. A survey was conducted in an office building in France between December 19, 2016 and September 25, 2017. A total of 93 occupants participated in the study. The relationship between participation ratio and the occupant related factors were analyzed via Kruskal-Wallis tests. The results show that the energy awareness level has a statistically significant effect on the survey participation ratio whereas gender and age group have not a significant effect on the survey participation ratio. Therefore, this result is a proof that the energy awareness levels of occupants have to be increased in order to reach higher participation ratios.
Reducing Domestic Energy Consumption using Behavioural Economics, Evaluation of Three systems
Alejandro Guzman Botero, Cristina Nan
Domestic energy use represents almost a quarter of the global carbon emissions. While the development of clean energies and implementation of better public policies are critical, reducing energy consumption in households represents a significant step towards a sustainable future. Improving domestic energy consumption behavioural patterns offers, among others, an important way to achieve such reduction. This paper presents a research on the different biases that shape people’s behaviour, decision making, habits, and motivation. Then, three cases of existing products that address domestic energy consumption are studied and analyzed using a set of parameters based on the previous research.
A Framework of Occupant Behavior Modeling and Data Sensing for Improving Building Energy Simulation
Mengda Jia, Ravi S. Srinivasan, Robert Ries, Gnana Bharathy
Studies have shown the influence of building occupants on building energy use. However, current building energy simulation tools lack dynamic and realistic occupant information inputs in modeling. The development of a robust occupant behavior model that can generate occupant schedules for use in building energy simulation algorithms will have the potential to improve accuracy of energy estimation. One such approach is the use of Agent-based Modeling (ABM) which has been successfully applied to model interactions between occupants and building systems. Yet, most of the models were developed with simulated data rather than actual data inputs from indoor environment. This paper proposes a framework for tracking indoor environmental data and occupant-building system interactions to model occupant behaviors in educational buildings using ABM. The data collection approach combines both smart sensor node deployments and paper-based surveys for future validation of the framework. A pilot study is conducted to explore the effectiveness of the framework. The results show the feasibility of integrating ABM for occupant behavior modeling to obtain improved energy use estimates.
Observed Behaviours in Simulated Close-range Pedestrian Dynamics
Omar Hesham, Princy, Walter Aburime, Ziyad Rabeh, Shashi Bhushan, and Gabriel Wainer
Crowd simulation can be a useful tool for predicting, analyzing, and planning mass-gathering events. The analysis of simulated crowds aims to extract observations to assess occupant interactions and potential crowd flow issues. This paper presents a continuous-space definition of Centroidal Particle Dynamics (CPD) crowd models, then proceeds to present behaviours observed in the simulated crowds. These include organized micro-grouping (flocking), uncooperative behaviors like passage blocking and collisions due to distracted pedestrians. It also briefly explores how spatial design choices could positively impact pedestrian flow. The observations might be of interest to designers of urban and architectural spaces who are looking to improve pedestrian or occupant experience, particularly in high-density crowd scenarios. The presented CPD method is additionally implemented to run on mobile (Android) devices, allowing on-the-field crowd simulation for event planning.
Organic Architectural Spatial Design Driven by Agent-Based Crowd Simulation
Mahdiar Ghaffarian, Roxane Fallah, Christian Jacob
This paper seeks the development of a tool for generation of architectural space through an organic form finding process by using agent-based behavior systems. A combination of architectural design, computation and biology is explored in this research, where the design is informed by dynamic data, and emerging behaviors are envisioned as biological phenomena. This computational design algorithm has two major aspects; the agent-based crowd simulation, that produces the dynamic simulation system and explores ways to control the output in a meaningful way. And form generation, that translates the movement data from simulation into high resolution, soft and dynamic geometry that could be envisioned as architectural form. The goal is to employ crowd simulation to produce the natural circulation patterns and use the negative space as functional program space. In order to do so, the system will receive a functional program as input data, that will be translated into the agent-based world components, then the agent-based crowd simulation program will generate the circulation patterns. In the next step, the crowd simulation movement pattern will be translated into architectural form through a generative design process, where the final result is a 3D spatial design product as the output of the system. A form that is generated by human movement and creates a space that accommodates the same human behavior.
Human Task and Disability Based Automated Evaluation of Space and Design in CAD
Mathew Schwartz, Adara Azeez and Kanisha Patel
As data continues to influence every field, including creative ones such as architecture and design, the importance in the type of data increases. Through generative algorithms, or more recently machine learning, the mathematical formulas are designed to reduce, minimize, or optimize certain parameters. These parameters should have a method for evaluation in order to check the generated or created design option. It is this method of evaluating the design that is a critical underlying component that must be researched before implementing mass customized designs from computer algorithms. This paper discuses the use of human factors as an evaluation criteria, with the important assumption: the designed space is meant to be for people. A broad review of various human factors that have been quantified in literature is presented. Additionally, methods for parsing a building design when geometry is not organized, as in the case of BIM, are detailed. Examples of human factors related to designed spaces of various people are given, along with specifics in how the presented evaluation methods can be applied to improving space for people, including some with disabilities.
A Dashboard Model to Support Spatio-Temporal Analysis of Simulated Human Behavior in Future Built Environments (Short Paper)
Michal Gath-Morad, Einat Zinger, Davide Schaumann, Nirit Putievsky Pilosof Yehuda E. Kalay
Current approaches and tools for simulating human behaviour in built environments generate complex, voluminous spatiotemporal datasets describing the mutual interactions between human agents and virtual spaces over time. Despite the immense potential of these tools and the data they generate to inform architectural design decisions, a potential barrier that may hinder their integration in architectural design processes is the difficulty to analyze and interpret the simulated behaviour output in a meaningful way. To address this challenge, the paper presents the preliminary development and implementation of an analysis dashboard model used to analyse and dynamically visualize spatio-temporal behavioral data to support informed design decisions. To elucidate the potential contribution of the proposed dashboard model, we implement it to support a comparative analysis of the same simulated narrative in two systematically varied medical wards. Despite the fact that the spatial variation between both medical wards is rather nuanced, initial results showcase the dashboard’s ability to quantify and spatially visualize the subtle, yet meaningful performance differences between both layouts over time and space. Finally, the dashboard’s limitations as well as future research directions are briefly discussed.
Structural Sculpting: A designer approach to robotically carved stone structures
Joseph Choma
This research combines mathematical form-making and structurally derived logic to develop a new approach to designing globally compression-only stone structures. Instead of following canonical geometric principles of catenaries or arches, the parametric equation of a dome was systematically manipulated into a structural geometry that has to yet be classified according to traditional frameworks. The design was structurally analyzed according to deflection, stone stresses and principal forces (compression and tension). Unlike traditional masonry structures, structural stone does not need to be constrained to one repeating unit. With advancements in robotic fabrication, blocks of stone can be carved into thin doubly‐curved surfaces with intricate shear key joints. Although stone is an ancient building material, designing robotically carved stone structures is a relatively young discourse. This paper documents a collaboration between Joseph Choma (designer), Quarra Stone Company (fabricator) and Bruce Danziger and Allan Olson at Arup (structural engineers). The research project is a 12’ x 7’ x 6’ structure composed of six pieces which are connected through dry (stone on stone) friction fit (shear key) joints. Within the design, no steel rods or adhesives are used. The surface thickness of the piece tapers from 6” at the base to 1.6”. Although the project is not fully realized, a robotically carved physical mockup and finite element analysis serve as a proof-of-concept to this research exploration.
Robotic Fabrication of Segmented Shells: Integrated Data-Driven Design
Elena Shilova, Mithuna Murugesh, Michael Weinstock
This paper proposes a strategy for constructing unreinforced segmented shells with the aspiration to bring together several related research fields. By incorporating data from structural analysis and digital simulations into a continuous workflow, an automated building system is introduced. The research aims to provide a methodology of translation between digital form-finding, optimisation strategies and physical materialisation by persisting through the interdependent stages of design and robotic assembly. Through an integration of structural analysis data, a force- driven form-finding process is determined, accompanied by a custom tessellation pattern. System stereotomy is developed as an integrated interlocking system, derived from material properties and robotic fabrication constraints. Assembly process is developed as an automated construction ‘pick and place system’ capable of customized, on-site fabrication of architectural-scale structures. The system consists of multiple six-axis robotic arms, carried on mobile platforms with scissors lifts. The complexity of robotic manufacturing is addressed through developing a custom robotic toolpath. Correlations between these steps of the process are verified through developing a large-scale prototype, tested with proposed robotic assembly logic.
Using Interactive Evolution to Design Behaviors for Non-deterministic Self-organized Construction
Mary Katherine Heinrich, Payam Zahadat, John Harding, Mads Nikolaj Brandt, Emil Fabritius Buchwald, Leonardo Castaman, Kit Wai Chan, Malte Harrig, Stian Vestly Holte, Lynn Kieffer, Jens Lee Jørgensen, Chao-Yuan Liang, Erik Lima Skjæveland, Sofie Lund Michaelsen, Viktoria Millentrup, Suna Petersen, Martin Petrov, Enrico Pontello, Fabian Puller, Gabriella Rossi, Johanne Marie Skalle, Sofia Stylianou, Alma Bangsgaard Svendsen, James Walker, Paul Nicholas and Phil Ayres
Self-organizing construction is an emerging subdomain for on-site construction robots. This not only presents new challenges for robotics, but due to the stochasticity involved in such systems, impacts the modeling and prediction of resulting built structures. Self-organizing models have been explored by architects for generative design and for optimization, but so far have infrequently been studied in the context of construction. Here we present a strategy for architects to design with non-deterministic self-organizing behaviors, using interactive evolution to incorporate user judgment. We introduce our “Integrated Growth Projection” method, having implemented it into a software pipeline for early phase design. We test the software with an initial user group of architects, to see whether the method and pipeline helps them design a non-deterministic self-organizing behavior. The user group creates several hybrid controllers that reliably solve their chosen design tasks.
Responsive Kirigami: Context-Actuated Hinges in Folded Sheet Systems
Jingyang Liu, Jasmine (Chia-Chia) Liu, Madeleine Eggers and Jenny E. Sabin
This paper explores the possibilities of active kirigami geometry — folding with the addition of strategically placed cuts and holes — through geometry, simulations, and responsive materials exploration. We have developed a novel method for kirigami pattern design through mesh optimization of surfaces, distribution of tucks across the discretized mesh, and the addition of cut and fold patterns. Based on our previous materials research on dual composite kirigami materials in 2016, we propose to focus on both oneway and two-way actuated materials, including shrinky dink films, shape memory alloys, and shape memory polymers. We have successfully characterized the materials, and as a proof of concept, produced models that utilize the abovementioned materials as environmentally-actuated hinges in folded sheet systems (2D to 3D).
Urban Glitch: A VR platform for participatory design
Eleni Polychronaki, Maria Christina Manousaki, Maria Aceytuno Poch and Giovanna Carolina Perea Ore
The aim of this research is to examine a new approach of participatory design using a virtual reality (VR) platform, in an attempt to enhance the communication between designers and users, while targeting the issue of unused public spaces in densely populated cities in general and London in particular. Initially, a detailed analysis of London’s urban tissue, pointed out a test location in Hoxton, characterised by a poor public space quality and a strong community feeling. Subsequently, a public survey was carried out, providing substantial information on the spatial needs of the residents and informing the development and guidelines of the VR platform. Built in a single-player mode, the game enables participants to create their own design proposals, through a modular design logic, within a virtual realistic representation of the site. The game was tested in a public workshop by approximately 65 participants, of multiple backgrounds. Once analysed and processed, the results were transformed into a data package that was released together with a design brief to architects in a social media event. The reception of six design proposals signified the first step towards validating the efficiency and applicability of the proposed design method. Given the initially linear character of the process and lack of iterative interaction among designers and users, the next steps of the research will aim to enhance the method, including a feedback loop participatory activity within a multi-player VR platform.
Auto-Calibrated Urban Building Energy Models as Continuous Planning Tools (Short Paper)
Shreshth Nagpal, Jared Hanson and Christoph Reinhart
Owners of large building portfolios, such as university campuses, increasingly rely on physics-based building energy models, calibrated to historic energy data, to explore energy efficiency retrofits. These calibrated models, which require substantial effort to originally set up, are then typically only used once for analyzing a series of upgrade options. This paper presents a methodology for the development of a continuous energy performance tracking system that expands the point-in-time analysis capabilities of conventional urban energy modeling platforms. The goals are to enable university campuses to manage their building energy-use over time by automatically tracking their actual performance against earlier defined targets, updating individual building energy models following the implementation of any upgrades and evaluating potential future retrofit strategies. A key innovation is the development of easy to implement workflows that are cognizant of current flows of information and that allow the mapping and display of changes and their consequences.
Cellular Automata: Bridge between Building Variability and Urban Form Control
Barbara Andrade Zandavali and Benamy Turkienicz
In Porto Alegre, a Brazilian town with 1,5 million inhabitants, zoning guidelines assign similar density parameters but fail to be context-specific. As urban regulations are closely linked to individual plot dimensions, the physical growth outcome ends up by being a heterogeneous and unpredictable urban space. Floor Space Indexes (FSI) had been used as physical currency which influences the plot value there hence creating a straightjacket to architects wanting to explore new building shapes. This article describes a simultaneous top-down and bottom-up strategy to allow urban rules to emulate architectural flexibility and, at the same time, to empower the city with morphological controls over the urban space. A proposed integrated model was set to generate a wide variety of geometries through the association of morpho-types urban blocks (top-down) to bottom-up strategies using cellular automata as a generative tool. The model includes context sensibility and daylight evaluation and runs with a similar FSI to the existing urban regulations. The experiment, which has used a dataset originated in the city of Porto Alegre has indicated possible paths for the creation of innovative urban indexes as building’s porosity which could be used in any geographical setting.
Generative Urban Design: Integrating Financial and Energy Goals for Automated Neighborhood Layout
Danil Nagy, Lorenzo Villaggi, and David Benjamin
This paper demonstrates an application of Generative Design to an urban scale through the design of a real-world residential neighborhood development project in Alkmaar, Netherlands. Problems in urban design can benefit greatly from the Generative Design framework due to their complexity and the presence of many stakeholders with various and potentially conflicting demands. We demonstrate this potential complexity by optimizing for two important goals: the profitability of the project for the developer and the potential for energy generation of solar panels placed on the roofs of the buildings. This paper points to further research into the application of the Generative Design framework to solve design problems at an urban scale.
Simulation of Urban Microclimate with SOLENE- microclimat - An Outdoor Comfort Case Study
Clément Imbert, Sagnik Bhattacharjee, Jiří Tencar
There are numerous physical phenomena that occur in an urban microclimate which need to be taken into account for simulating outdoor comfort. However, very few tools are dedicated towards this cause. The objective of this article is to present the assessment of the impacts of different urban strategies on a simulated neighbourhood microclimate. The neighbourhood is located in Prague, Czech Republic, and its microclimate was simulated using a simulation tool called SOLENE-microclimat. It consists of a coupling of a thermo-radiative model, a thermal building model and a computational fluid dynamics model (CFD). One of its purposes is to simulate the impact of urban built environment on outdoor comfort. The obtained simulation results are based on two variable parameters: surface albedo and presence of trees. These results include variations in surface, air temperatures, wind speeds and the Universal Thermal Climate Index (UTCI) in the given urban area. The analysis shows that both variations have a significant impact on the urban microclimate. The potential use of this simulation tool for urban built environment is discussed along with its limitations. Such kind of studies can be important for city planning, i.e. providing thermal comfort in urban built environment and mitigating urban heat island.
Validation and Comparison of Different CFD Simulation Software Predictions of Urban Wind Environment based on AIJ Wind Tunnel Benchmarks
Jing Li, Aymeric Delmas, Michael Donn and Riley Willis
This study reports the results of calibrating three CFD programs against experimental wind tunnel data. Accurate simulation of outdoor wind flow is essential for designing comfortable and safe urban spaces. With the increasing availability of Computational Fluid Dynamics programs, this type of simulation is becoming more feasible for general urban design practice. In fact, given the potential to digitally combine solar radiation and temperature simulation data, a comprehensive analysis of urban outdoor comfort and of indoor ventilation quality is now feasible for a much wider range of buildings and urban spaces. The quality assurance of the simulation remains however paramount. It has been common for new wind tunnel facilities to test their prediction abilities against a standard, high-quality dataset. One such dataset is provided by the Architectural Institute of Japan (AIJ). This research paper reports the urban flow regimes or effect areas where the CFD programs agree with each other; the parts where they agree with the wind tunnel data; and the parts where they disagree. The implications of these trends for the reliability of CFD-based design decisions are discussed.
Urbano: A New Tool to Promote Mobility-aware Urban Design, Active Transportation Modeling and Access Analysis for Amenities and Public Transport
Timur Dogan, Samitha Samaranayake, Nikhil Saraf
Rapid urbanization, with new global construction estimated to be 250 times the floor area of NYC by 2050, is increasing traffic congestion, pollution and related health threats. This is a worrisome development but also a unique opportunity to improve urban mobility and quality of life. Understanding consequences of urban design choices on mobility, sustainability, and health is a necessity and requires development of a framework that enables such co-design processes. Existing transportation modelling tools are detached from the design process as they require technical expertise in traffic modelling, extensive preprocessing steps and heavy computational power, all of which make it difficult to be accessed by urban planners and designers. We propose a new, easy to use, CAD integrated, design-toolkit, called “Urbano”, to model active transportation and to evaluate access to amenities and public transport. Urbano introduces a fully automated workflow to load in contextual GIS, OpenStreetMap and Google Places data to set up an urban mobility model. Kicking off by computing validated walkability metrics like a more flexible and modifiable version of the Walkscore, the tool will include other urban scale mobility metrics to aid the urban design process.
Data-driven State Space Reconstruction of Mobility on Demand Systems for Sizing-Rebalancing Analysis
Dimitris Papanikolaou
Computer-supported scenario analysis is a fundamental practice in urban planning in which a decision-maker formulates a question and a computer model simulates the hypothetical scenario for subsequent assessment. This paper concentrates on scenario analysis for sizing and rebalancing tradeoffs for mobility on demand (MoD) systems. Developing such models is challenging because trip patterns are by definition random while rebalancing patterns require first solving routing, a computationally intractable problem even for medium-sized systems. Using Boston’s bike sharing system as a case, we present a novel approach based on reconstructing accumulation dynamics, showing that, independently of system or trip pattern characteristics, vehicle mass in MoD systems moves periodically between two types of locations and accumulates between two other types of locations. Following this, we present a method to build data-driven system dynamics macromodels that allow decision makers to interactively explore scenarios like: by how much will traffic, fleet, or parking requirements change for a marginal change in rebalancing work? .
Modelling Approach for Building Cluster Scale
Ilaria Vigna1, Marco Lovati and Roberta Pernetti
This research proposes a modelling approach for building clusters as a support for the design of the renovation and the performance assessment of technologies and RES integration, taking into account the interaction between buildings and maximizing the use of RES at local scale. Starting from some archetypical cluster configurations defined according to a literature analysis framework, a simplified thermodynamic model will be developed in Modelica language and simulation will be carried out to generate the energy demand profile of a cluster. Then, an evaluation of the flexibility of the renovation strategies at cluster scale will be performed and coupled with an optimization of the PV installation, in order to optimize the energy matching at cluster scale. Finally, the identification of best mix of renovation strategies in clusters will be assessed through an extensive modelling campaign. The use of such modelling strategy will support advanced building designers in choosing and applying technologies and strategies for RES integration in early design phase of buildings.
System Dynamics for Modeling Metabolism Mechanisms for Urban Planning
Reinhard Koenig, Martin Bielik and Sven Schneider
Dynamic urban development simulation models are usually separate to urban planning tools making it difficult to test the consequences of urban planning variants directly without switching between expert tools. This paper presents an approach to integrating system dynamics simulation at various scales and abstractions in the visual programming environment Grasshopper for Rhino3D. We demonstrate how Grasshopper may be used with additional customized components as a flexible integrated urban planning and simulation framework. For this purpose, we present three urban planning model examples: The first is a classical system dynamics simulation that abstracts from spatial elements. The second adds spatial relations in terms of distances between locations in a grid. The third shows how to represent a city in more details and adds a network analysis module for more precise distance calculations. As result, we demonstrate a highly flexible approach for integrating simulations for various aspects that predict the behavior of an urban system in order to facilitate more sustainable urban planning processes. The main drawback of this new level of flexibility is the relatively slow execution time for complex simulations.
Quantifying the Urban Experience: Establishing Criteria for Performance Based Zoning
Luc Wilson, Jason Danforth, Dennis Harvey, and Nicholas LiCalzi
Exponential growth is pressuring cities around the world to reevaluate their management of new development. Challenges stemming from such growth, including crises in affordable housing and transit accessibility, see cities responding by constructing ever greater densities, a process limited by current zoning regulations. Traditional zoning frameworks are rigid and slow to adapt, making it difficult for development to keep pace with greater density requirements. By establishing certain baseline urban metrics tied to a set of performance standards, performance-based zoning allows cities to proactively accommodate growth and demand while mitigating potential negative externalities. One of the primary challenges for a truly performance-based zoning methodology is defining and calibrating desired performance standards. Cities must consider criteria associated with, for example, comfort, mobility, and activity in such a way that defines achievable, goal-oriented benchmarks– a difficult task given the complexity of urban systems. In proposing a process for creating a performance-based zoning framework, this paper: 1) explores urban analysis methods, focusing on urban comfort, mobility, and activity, to create new urban performance datasets for Manhattan for use in establishing new zoning protocols, and 2) develops new visualization techniques that can more effectively engage stakeholders, make data understandable and accessible for decisionmakers, and broaden the discussion to involve a wider range of non-specialist participants.
Radiant Image based data post-processing and simulation
Navid Hatefnia, Marjan Ghobad
A precise methodology to capture and analyse environmental data provides a possibility to improve the spatial design regarding its comfort condition. In this regard, this paper aims to improve the understanding of environmental parameters by employing the cutting-edge recording and analytical image-based data post-processing methods. The image data processing method is used to capture and analyse the radiant ambient data. These methods provide a detailed, comprehensive database to simultaneously capture different ambient parameters like geometrical features, surface radiation, surface temperature, etc. in a high-level resolution manner. Subsequently, the resulting database can be accessed for more in-depth analyses which could assist architects or urban designers to determine the most effective parameters on the thermal comfort. In addition, the database significantly expedites the process to estimate the involving factors in comfort at any time of the year. The presented technique optimally measures and records a large amount of data to distinguish the role of the environmental parameters and prepare a comprehensive foundation for further simulations. Consequently, all the information needed to estimate the thermal comfort at different points of an outdoor or indoor space over a year can be calculated by this technique using only few input data.
Identifying the Surface Materials of the Existing Environment through Point Cloud Data Attributes
Miktha Farid Alkadri, Michela Turrin, Sevil Sariyildiz
The prospective application of 3D laser data scanning provides numerous possibilities for investigating environmental performances for architectural design. One of the possibilities includes the practical usability of point cloud data in examining the existing environment. Exploiting this potential would help to increase the information on properties of the real context, which currently often lack during the conceptual design process. As part of this general goal, this research particularly investigates the potentials of the surface attributes contained in the point cloud data such as color, position, and intensity information. The extraction of this information allows mapping the distribution of surface materials of the existing environment by considering the intensity and the albedo values. The outcome of the research constitutes a catalogue of surface materials that are useful for architects as a decision support environments. In parallel with computational design flow, this research ultimately aims at delivering a novel method for architects to perform site analysis comprehensively.
Developing a Workflow to Integrate Tree Inventory Data into Urban Energy Models
Farzad Hashemi, Breanna Marmur, Ulrike Passe and Janette Thompson
Building energy simulation is of considerable interest and benefit for architects, engineers, and urban planners. Only recently has it become possible to develop integrated energy models for clusters of buildings in urban areas. Simulating energy consumption of the built environment on a relatively large scale (e.g., such as a neighborhood) will be necessary to obtain more reliable results, since building energy parameters are influenced by characteristics of the nearby environment. Therefore, the construction of a 3-D model of urban built areas with detail of the near-building environment should enhance simulation approaches and provide more accurate results. This paper describes the process of integrating urban forest inventory data into a 3-D energy model for a US Midwest neighborhood, including building footprint, parcel and tree data. This model was prepared for use in the Urban Modeling Interface (umi) tool to analyze the effect of tree shading on building energy performance. We used Grasshopper 3-D, the Meerkat plug-in, and GIS to integrate these datasets for model generation.
An Image-based Method to Evaluate Solar and Daylight Potential in Urban Areas
Christina Chatzipoulka, Raphael Compagnon and Jerome Kaempf
Solar irradiance and illuminance are important renewable resources that can significantly increase buildings’ energy efficiency, associated to solar passive and active techniques and use of daylighting. In addition, it is widely acknowledged that the presence of natural light and some sunlight indoors is essential for inhabitants’ well-being. This paper presents a new method to assess solar and daylight availability in the built environment at different scales. The method is based on two types of images where the mutual obstruction between neighbouring buildings is represented over stereographic projections of the sky vault. The images can be used in two ways, either for the visual assessment of the examined surface(s) or, to be processed as to obtain a series of numeric performance indicators. In both ways, they can be combined with similar projections of the sun path or sky radiance/luminance distributions, for considering locations’ latitude and climate, respectively. To exemplify the use and relevance of the tools, especially at the early-design stages, the method is applied to compare the proposals submitted in a masterplan competition. The five finalists are examined in relation to the performance of their facades and roofs, as well as their impact on an existing fac¸ade. Last, a targeted analysis showed a good correlation between performance indicators, readily computed by the method, and predicted annual energy demands.
CitySeek: Towards Urban Daylight Models based on GIS Data and Semi-automated Image Processing
Timur Dogan and Maksis Knutins
Recent trends promote living and working in high-density urban areas. Increased urban density, however, leads to a conflict between space-use efficiency and daylight access. Daylighting has been linked to energy efficiency and health and is often mentioned in relation to quality of space and real estate value. As daylight is becoming a resource of growing interest, cities need to include daylighting related performance indicators in their GIS datasets. To manage daylight related conflicts, cities have traditionally relied on zoning guidelines proposing simple, two-dimensional geometric evaluation techniques without ever directly measuring climate-based daylight availability. While simulation tools to model urban daylight availability exist, GIS datasets often lack key information needed for the simulation setup. This paper presents an approach towards building urban daylight models using GIS data and semi-automated image processing to capture window to wall ratios of building facades. As a case study, a speculative urban daylight model (UDM) for West Village in New York City is presented.
The Urban Scale
Dan Macumber, Amber Bartosh, Danil Nagy, David Gerber and Timur Dogan
People currently live in urban areas more than ever before in human history. Cities are built and continue to grow at an unprecedented rate, along with a myriad of negative effects linked to urban living that include building energy inefficiency, consequent increase in carbon emissions and its effect on climate change exacerbation. The role urban design plays in mitigating built environment impacts is critical. This panel tackles the role of Urban Building Energy Models (UBEMs) to support urban design decisions. The panel will explore UBEMs in practice and ask the question: how can UBEMS effectively simulate multiple performance measures to inform design decisions and energy policies? What is the state-of-the-art in this rapidly growing area of research? The premise is there is an urgent need to improve urban-scale energy efficiency and integrating renewable electricity sources, while enhancing the lives of individuals and communities that consume, and in some cases, produce energy.