Program
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Invited Talks
Cyber-Physical Systems and Open Data Platforms
Dennis Shelden – Georgia Tech
The past two decades have marked a proliferation of modeling and simulation capabilities in architecture, engineering and construction (AEC), enabling radical advances in efficiencies of production, expanded geometries, improved simulation capabilities, and cross process data exchange and collaboration. These advances provide the base capabilities for an emerging set of next generation advances, driven by the development of large scale, integrated digital-physical (“Cyber-Physical”) systems, connecting the built environment to simulation and analytics in real time over cloud and IoT technologies. New research agendas that integrate information sciences, systems and sensing with traditional built systems design and engineering to support the development of scalable intelligent Cyber-Physical systems will be among the central drivers of next generation of the building industry. This presentation will focus on specific technical, organizational and cultural advances supporting the expansion of the AEC agenda into the design, delivery and operation of intelligent building systems and environments.
Presenter Biography
Dennis Shelden is an Associate Professor of Architecture and Director of the Digital Building Laboratory at Georgia Tech. He is an expert in applications of digital technology to building design, construction, and operations, with experience spanning education and research, technology development, and professional practice across architecture, engineering, and computing disciplines. He directs Georgia Tech’s Ph.D. in Architecture and M.S. in Architecture: Building Information and Systems Concentration programs. Prior to joining Georgia Tech, he led the development of architect Frank Gehry’s digital practice, first as Director of R&D and Director of Computing, and subsequently as Co-founder and Chief Technology Officer of the technology spin off Gehry Technologies. He was an Associate Professor of Practice in Computation and Design at MIT from 2005-2015 and has taught at UCLA and SCIARC. He holds a B.S. in Architecture, an M.S. in Civil and Environmental Engineering, and a Ph.D. in Architecture: Computation and Design from MIT, and he is a licensed Architect in California.
Dr. Shelden’s research broadly concerns the role of advances in digital modeling and information management in the development and operation of built systems and in the evolution of practice. He has specific expertise in the integrated design, delivery, and operations of large-scale, complex buildings and building systems. Within this broad field of application, Dr. Shelden’s current research focuses on four topics: integrated project systems; smart buildings, infrastructure, and environments; open data standards and building industry data platforms; and process and practice transformation.
The Future of Thermal Comfort in a Warming Climate
Stefano Schiavon – University of California Berkeley
We spend most of our time in built spaces that substantially affect our health and well-being and the built environment has a large influence on climate change, mainly due to the energy we use to keep acceptable levels of indoor comfort. In this presentation, I will show that we are still systematically measuring high thermal dissatisfaction, even in green and high performance buildings, and that the thermal comfort models that we use for designing buildings have low prediction accuracy. How can we enhance occupant satisfaction without increasing our environmental impact? Personal comfort systems are individually controlled micro-environmental systems that improve thermal comfort to suit the needs of occupant. Personal comfort model is a new approach to thermal comfort modeling that predicts individual thermal comfort responses, instead of the average response of a large population and it can be applied to any HVAC system. Personal comfort systems and models have the potential to increase comfort and reduce energy use.
Presenter Biography
Stefano Schiavon, PhD, is Associate Professor of Architecture at UC Berkeley and Associate Director of CEDR. Stefano’s research is focused on finding ways to reduce energy consumption in buildings and, at the same time, increase occupant health, well-being and productivity. Stefano works on thermal comfort, radiant systems, occupant satisfaction, underfloor air distribution (UFAD), air movement, personal comfort systems and models, LEED, energy simulation and statistical modeling. At the University of Padova he received a PhD in Energy Engineering, and a MS in Mechanical Engineering. He has been a visiting scholar at Tsinghua University and DTU. He received the 2010 REHVA Young Scientist Award and 2013 ASHRAE Ralph Nevins Award
Wait, What?
Billie Faircloth – KieranTimberlake
For more than a decade, KieranTimberlake has leveraged computation and simulation as a means to bridge gaps in architectural knowledge. As a transdisciplinary practice with individuals from fields as diverse as urban ecology, chemical physics, architecture, and sculpture, the firm’s models have become the means to explore design opportunities at the interface of disciplines and socialize knowledge normally bound to a single discipline. The firm’s modeling process is as much technical as it is social: It requires firm members to productively grapple with questions surrounding acceptable data sources, data coarseness and granularity, and levels of knowledge abstraction—simultaneously through the lens of multiple disciplines. KieranTimberlake Partner and Research Director Billie Faircloth will dissect examples of her firm’s models and share insights from ten years of pursuing a transdisciplinary modeling practice.
Presenter Biography
Billie Faircloth is a practicing architect, educator, and Partner at KieranTimberlake, where she leads transdisciplinary research, design, and problem-solving processes across fields including environmental management, urban ecology, chemical physics, materials science, and architecture. She fosters collaboration between trades, academies, and industries in order to define a relevant problem-solving boundary for the built environment. Billie has published and lectured internationally on themes including research methods for a trans-disciplinary and trans-scalar design practices; the production of new knowledge on materials, climate, and thermodynamic phenomena through the design of novel methods, tools and workflows; and the history of plastics in architecture to demonstrate how architecture’s ‘posture’ towards trans-disciplinary practices and new knowledge has changed over time.
Shape Matters
Dana Cupkova – Carnegie Mellon University and EPIPHYTE Lab
Energy has both empirical and perceptual qualities. Dana’s talk focuses on role of form in architecture to propose design strategies related to energy usage. Operating under the premise that complex geometries can be used to improve both the aesthetic and thermodynamic performance of passive heating and cooling systems, this line of inquiry tests the figuration of surfaces as primary actuators of heat transfer in thermal mass. The intention is to instrumentalize principles that offer a wider range of design tactics in the choreography of thermal gradients between buildings and their environment, while mitigating overuse of mechanical systems in buildings by offering insights into shape-making.
Presenter Biography
Dana Cupkova is a Co-founder and a Design Director of EPIPHYTE Lab, an interdisciplinary architectural design and research collaborative. She currently holds Assistant Professorship at Carnegie Mellon University - School of Architecture and serves as a graduate program Track Chair for the Master of Science in Sustainable Design (MSSD). She has been a member of the ACADIA Board of Directors since 2014-2018, and currently serves on the Editorial Board of The International Journal of Architectural Computing (IJAC).
EPIPHYTE Lab is a design practice immersed in interdisciplinary research, testing material behaviors and design processes that directly engage the inevitable computerization of our environment, and provoke a series of critical questions about the overlaps between technology, environment and perception. Dana’s designs explore the built environment at the intersection of ecology, computational processes, and systems analysis. In her research, she interrogates the relationship between design-space and ecology as it engages computational methods, thermodynamic processes, and experimentation with geometrically-driven performance logics. Her design work has been published internationally and presented at many academic conferences. In May 2018 Epiphyte Lab received the Next Progressives design practice award by ARCHITECT Magazine, The Journal of The American Institute of Architects.
Paper Abstracts
Sun and Wind: Integrated Environmental Performance Analysis for Building and Pedestrian Comfort
Francesco De Luca
Solar access and pedestrian wind are important factors for the design of comfortable dwellings and livable urban areas. At the same time they influence the shape and image of cities. Daylight is the most appreciated source of building interiors illumination. Urban wind can significantly increase the discomfort of pedestrians for its mechanical action around buildings. In Estonia the daylight standard regulates access to sun light. Different pedestrian wind comfort criteria exist. This paper presents a research work which analyzes the performance of direct solar access according the Estonian daylight standard and pedestrian wind comfort according the Lawson criteria of 27 building cluster variations in the city of Tallinn. A method which integrates different building and urban performance analysis is developed. Results show different optimal patterns for each environmental performance, though significant trade-offs are found, and critical periods of the year for pedestrian wind comfort.
A Parametric Workflow to Concieve Facades as Indoor and Outdoor Climate Givers
Emanuele Naboni, Eric Danzo and Luca Ofria
Within the bounds of climate change, it is legitimate to expect that buildings will be developed to mitigate and adapt to environmental transitions. In this context, façades are essential as they are not the only determinants in reducing energy demand, but could increase the livability of both indoor and outdoor spaces. Being that there are simulation tools which allow indoor comfort simulation, and others that enable outdoor comfort simulation, it is rare to find tools that allow simulation of both. Filling this particular gap, the present research develops a Ladybug Tools based digital workflow, which simultaneously accounts for indoor and outdoor thermal and visual parameters. Once created, the workflow is tested and calibrated against real-life measurements of indoor and outdoor Mean Radiant Temperature and Illuminance as values, via the use of a test room equipped with specific sensors. It is concluded that the workflow allows for the conception of a façade intended as a dual climate giver, for both the outdoor space and the indoor.
Streets, Parks & Plazas: Analyzing Daylight in the Public Realm
Elizabeth de Regt and Timothy Deak
Research has shown how integral daylight access is to both physical and mental health. While this has gained traction within building interiors, very little research has delved into the daylight that hits streets, parks, courtyards, and other exterior spaces that impact the urban experience. This paper provides a better understanding of how daylight affects these spaces and suggests a framework for the design of livable cities. 276 unique respondents answered a questionnaire. The results were utilized to qualitatively analyze the impact of daylighting within 25 well-known exterior urban spaces on city-users. Computer modeling, daylight simulation, and both correlation and regression analyses tied these respondents’ answers to quantitative data. New metrics, both data-driven and graphic, were used to summarize the daylighting qualities of these spaces, allowing designers to use these spaces and metrics for future comparison analyses. Given further exploration into the use of these metrics, they may also be applied to future zoning code alterations by providing the framework for a performance-based compliance path for achieving necessary daylighting at grade. Public and private sectors, from individual buildings to large-scale master plans, may utilize these metrics to create benchmarks for improving the urban experience.
Unleashing the Diversity of Conceptual Building Renovation Design: Integrating High-Fidelity Simulation with Rapid Constraint-Based Scenario Generation
Aliakbar Kamari, Carl Peter Leslie Schultz and Poul Henning Kirkegaard
Designing a renovation plan for a building is a highly complex task: during this planning process, the design team needs to explore an enormous “design space” of possible renovation actions, and on the other hand, must evaluate the efficacy of each candidate design using computationally expensive simulations. Moreover, the design team seeks to balance a range of competing key performance indicators (KPI) as demanded by clients and the real conditions of the existing buildings, which are unique for every project (e.g. energy consumption, daylight, and thermal comfort). We present an innovative renovation decision support framework that provides the design team with broad coverage of the design space in conjunction with limited, careful use of precise simulations for KPI evaluation. Our approach integrates logic-based domain model querying and multi-objective optimization based on Answer Set Programming and the KPI simulation system. We empirically evaluate our system in a large residential building case study in Denmark.
Application of Surrogate Modeling to Multi-Objective Optimization for Residential Retrofit Design
Arfa N. Aijazi and Leon R. Glicksman
This project combines surrogate modeling, a supervised machine learning technique, to bypass whole building energy simulations to enable multi-objective design optimization. We applied this method to identify Pareto optimal retrofit designs that are energy and cost effective for three residential apartments in Lisbon, Portugal. As part of our validation of this approach, we compared the surrogate model error for these Pareto optimal designs to the error in the rest of the design space when compared to a detailed energy simulation. Surrogate model error is higher towards the minimum and maximum energy consumption within the Pareto optimal designs compared to the rest of the design space. We also find that in the Pareto optimal set some design variable values are near their minimum or maximum value, which could be driving higher surrogate model error. We propose that future research should retrain the surrogate model after identifying design variable values of interest from an initial optimization run.
Aerial Thermography as a Tool to Inform Building Envelope Simulation Models (Short Paper)
Norhan Bayomi, Shreshth Nagpal, Tarek Rakha, Christoph Reinhart and John E. Fernandez
The building sector consumes more than 33% of global energy use and around 50% of electricity consumption, and is responsible for one third of global carbon emissions. Envelope and windows alone impact over 50% of energy loads in buildings. Thus, understanding building envelopes’ thermal performance is critical to the application of energy efficiency retrofits. Through detecting main envelope thermal deficiencies and areas of deterioration, suitable energy management measures can be effectively determined. While simulation models are considered as reliable tools to understand building energy performance, they rely significantly on assumptions related to envelope performance. The main contribution of this paper stems from the proposed analysis framework, which integrates Unmanned Aerial Vehicles (UAVs) equipped with thermal cameras in estimating thermal transmittance properties of existing building envelope, specifically opaque walls, and using these data to calibrate energy simulation models for better predictions. Results revealed a significant increase in the accuracy of heating energy use prediction during winter months. With the proposed workflow, simulation errors were reduced from over 20% to less than 1%.
Towards Assembly Information Modeling (AIM)
Ayoub Lharchi, Mette Ramsgaard Thomsen and Martin Tamke
Nowadays digital tools support architects, engineers and con-structors in many specific tasks in the construction industry. While these tools are covering almost all aspects of design and manufacturing, the planning and design for the assembly of buildings remain an unexplored area. This research aims to lay the foundations of a new framework for the design for as-sembly in architectural applications entitled Assembly Infor-mation Modeling. In practice, it is a central digital model con-taining the structure architectural design, construction details, three dimensional representations, assembly sequences, issue management and others. This framework forms the base for a multitude of novel applications for assembly design, plan-ning and execution, such as assembly simulation and strate-gies communication, problem detections in the early design phases and interdisciplinary coordination. This paper de-scribes the specifications of the digital assembly model and illustrate two use cases: collaborative assembly design using AEC cloud-based platforms and Augmented Assembly using Augmented reality devices.
Subjective Impressions of a Space Influencing Brightness Satisfaction: an Experimental Study in Virtual Reality
Azadeh Omidfar Sawyer and Kynthia Chamilothori
This paper investigates the relationship between participants’ satisfaction with brightness and other key perceptual attributes of the scene to gain insight in how user satisfaction with brightness is influenced by factors other than brightness levels. In this study, a total of 100 participants were immersed in an office space using virtual reality (VR). The brightness level in all immersive scenes were held constant while the office shading system’s design pattern, rendering materials, and furniture were varied to examine how different factors influence the participants’ satisfaction with brightness. Statistical analyses indicate that there is a strong association between participants’ satisfaction with brightness and other perceptual attributes. Additionally, while the effect of furniture on brightness satisfaction was not statistically significant, the analyses revealed that colored materials had a significant effect on participants’ evaluations of their satisfaction with brightness.
Immersive Representation of Urban Data (Short Paper)
Amber Bartosh and Rongzhu Gu
Urban environments are not comprised solely of physical objects like buildings, infrastructure, and landscapes, but also invisible, but critically influential, information like traffic patterns, economic values, and energy use. This intangible overlay of quantifiable urban behavior is essential to understanding how cities function. Vast quantities of urban data are now widely available through online open source data repositories, but the raw data remains limited in its value to support informed decision-making unless it can be synthesized and represented in a meaningful fashion. This paper describes in-progress research exploring the spatialization and representation of urban data using virtual reality (VR). This research uses Manhattan as a test case for enabling users to access urban data immersively and interactively from multiple vantage points and scales. It describes the process for visualizing the city in VR, representing urban data three-dimensionally, and creating a user interface for data interaction while in the virtual environment. The paper identifies initial steps towards creating an immersive representation of urban data to effectively inform future urban planning initiatives and design decisions.
A Data-driven Framework for Urban Building Operational Energy Use Modeling
Narjes Abbasabadi
Accurate measurement and analysis of urban energy use is an essential step in development of low-carbon cities. However, there is a limited number of methods and tools for energy use modeling and prediction at urban or neighborhood scales. This article proposes a bottom-up data-driven framework for urban energy use modeling (UEUM) which localizes energy performance measurements and considers urban context. The framework addresses the urban building operational energy estimation through the use of disaggregated energy use data and allows for an accurate urban energy performance measurement at building-level. A machine learning approach is applied to mathematically associate building characteristics and urban context attributes; i.e., building height, as an urban intensity metric, and sprawl indices representing compactness and connectivity of neighborhoods with urban building operational energy use intensity (EUI). Once the mathematical relationship is identified, the model predicts the energy consumption of individual buildings that represent a particular end-user. Chicago as a pilot case study was selected to test the framework. Several algorithms are tested and then the improved model was used to predict energy use for around 820,000 buildings in the city. The framework has the potential to aid designers, planners, and policymakers in a better understanding of the existing urban energy use profile, and the environmental impacts of alternative scenarios of urban development.
An Integrated Urban Planning and Simulation Method to Enforce Spatial Resilience Towards Flooding Hazards
Julius Morschek, Reinhard König, and Sven Schneider
Urban development projects in flood-prone areas are usually complex tasks where failures can cause disastrous outcomes. To tackle this problem, we introduce a toolbox (Spatial Resilience Toolbox – Flooding, short: SRTF) to integrate flooding related aspects into the planning process. This, so called toolbox enables stakeholders to assess risks, evaluate designs and identify possible mitigations of flood-related causes within the planning software environment Rhinoceros 3D and Grasshopper. The paper presents a convenient approach to integrate flooding simulation and analysis at various scales and abstractions into the planning process. The toolbox conducts physically based simulations to give the user feedback about the current state of flooding resilience within an urban fabric. It is possible to evaluate existing structures, ongoing developments as well as future plans. The toolbox is designed to handle structures in a building scale as well as entire neighborhood developments or cities. Urban designers can optimize the spatial layout according to flood resilience in an early phase of the planning process. In this way, the toolbox can help to minimize the risk of flooding and simultaneously reduces the cost arising from the implementation and maintenance of drainage infrastructure.
A Method for Integrating an UBEM with GIS for Spatiotemporal Visualization and Analysis
Bess Krietemeyer and Rawad El Kontar
Leveraging Geographic Information Systems (GIS) for spatiotemporal visualization and analysis of simulated UBEM datasets and real-world data simultaneously can assist in identifying opportunities, as well as potential barriers, to energy efficient and climate adaptation strategies. However, current GIS-based models that support interactive exploration of adaptation strategies and future scenarios are scarce and do not easily incorporate building energy use data for visual analysis over time. This paper describes a workflow to integrate simulated building energy consumption data associated with variable energy efficiency scenarios within a GIS platform for interactive spatiotemporal visualization to support climate adaptation decision-making. The contribution of the work presented is in the ability to selectively view and analyze simulated building energy performance data layered with other real-world geospatial data through an automated feedback loop between an UBEM and ArcGIS. An interactive interface is designed in ArcGIS to enable users to explore building performance scenarios spatially and over time. Using a downtown neighborhood in Syracuse, New York, USA, as a case study, preliminary results demonstrate how the workflow provides insight into existing energy use issues and potential for implementing strategies such as energy load shifting or building retrofits. A discussion includes opportunities as well as challenges to the workflow in facilitating understanding of urban energy model outputs by multiple stakeholders in evaluating potential energy efficient strategies.
A Technique for Developing High-Resolution Residential Occupancy Schedules for Urban Energy Models
Diba Malekpour Koupaei, Farzad Hashemi, Vinciane Tabard-Fortecoëf and Ulrike Passe
Occupants’ presence and activity schedules directly influence residential energy consumption loads. Regardless of their widely acknowledged importance, developing proper representative occupancy inputs for urban energy use studies of residential neighborhoods remains to be a challenge to overcome. The presented work aims to balance between accuracy and complexity of such occupancy models by developing a technique that takes advantage of a previously proposed sophisticated method for schedule generation and attempts to refine and simplify its results for practicality purposes. Here, we used a Markov chain transition probability matrix based on the American Time-Use Survey (ATUS) database and selectively refined its outputs according to the data collected from our own designated population of study. The resulting refined schedules were incorporated into the Urban Modeling Interface (umi) interface and were then tested on our pilot case study, a relatively low-income dense neighborhood in the Midwestern United States composed of 272 residential buildings. An initial investigation of this technique’s performance suggests that while the use of the ATUS based model provided a high level of variability and sophistication, the customization step ensured that the resulting schedules are representative of our population and its characteristics. More importantly, we were able to maintain simplicity and practicality.
Environmental Data and Land Use: Integration of Site-Specific Ecology and Urban Design
Claudio Campanile and Shih Hsin Wuu
The aim of this research focuses on how site-specific environmental data and programme-defined relationships (land use and their relation) can work collaboratively to design an integral ecological urban fabric. The paper presents a work flow applied to a case study and is formed by three main parts: data collection and elaboration, land use pattern generation and design development for critics and insights. The case study consists of a design proposal for a city for 40,000 dwellers located along the South coast-line of Isle of Grain, UK. The area is mainly made up of marshlands and the project is envisioned in a near-future scenario in the likely event of land shortage and sea level rise. In the first part, design parameters such as areas and functions for hypothetical energy, food and site protection needs are defined. At the same time, environmental data is gathered for tide frequency, topography and water speed. A suitability-based evaluation criterion is introduced to relate land use and environmental conditions at a specific location within the site. In the second part, we investigate two methods for generating design options of land use distribution. As both methods rely on neighbour conditions, a principle of the cellular automata algorithm (CA), their implementations deviate fundamentally from CA, such as that all the land- uses generated within an iteration are quantitatively defined as a design parameter. The first methodology is based on a growing system, while the latter on a competing system. In the third and last part of the workflow, we select and carry forward one generated land-use pattern due to specific evaluation criteria and develop the design at urban scale: different building plots’ morphologies are generated depending on their location and degree of clustering. We conclude with critics and potentials, such as the applicability at different scales.
How to Generate a Thousand Master Plans: A Framework for Computational Urban Design
Luc Wilson, Jason Danforth, Carlos Cerezo Davila, and Dee Harvey
The current process for the design of an urban master plan typically involves a team of architects and urban planners that conceive and develop a handful of schemes based on zoning requirements with the help of CAD software. They may intend for the plan to achieve a set of performance goals (economic, environmental, etc.), but quantitative per-formance analysis is rarely conducted early and consistently through the design process. This makes it difficult to under-stand the full range of approaches that are possible on the site, and the relative performance of each scheme. In order to best accommodate rapid urbanization while making cities more sustainable, livable, and equitable, designers must uti-lize quantitative tools to make informed decisions about their designs. Computational design techniques have been success-fully used at the building scale to test numerous designs and quantify their performance, but are challenging to apply at the urban scale due to increased computational expense, dif-ficulty in limiting inputs, and more stakeholders involved in the process. This paper outlines a methodology developed in practice for applying computational design at the urban scale through four steps: 1) Define Inputs & Design Space 2) Procedural Geometry Generation, 3) Performance Evaluation and 4) Analysis, Communication & Stakeholder Engagement to generate and test thousands of master planning scenarios.
CityFiction – Scenarios for Densification
Henrik Malm and Petra Jenning
The aim of the research presented in this paper is to find new ways of understanding and visualising relationships between different types of city data, and thereby support decision making regarding city growth and densification based on desires and values. To this end, a new software tool called CityFiction has been developed. This analysis tool is intended to work as a laboratory for understanding city data, and it will be shown that by interactively weighting, or prioritizing, different measures on the available input data, scenarios for the future development of a city can be efficiently and pedagogically explored. By using the city of Malmö, Sweden, as a pilot study, the tool has been applied to test the placement of e.g. new parks and train stations, and it has aided in the understanding of how the available city data interacts, and possibly conflicts, in the search for a sustainable development of the city.
Exploring Urban Walkability Models and Pedestrian Movement Trends in a Vancouver Neighbourhood (Short Paper)
Nicholas Martino, Cynthia Girling and Edja Trigueiro
Walkability, or how inviting a place is to pedestrians, has proven a useful concept for urban decision-makers. Although there are now several methods to measure and evaluate the walkability of streets and neighbourhoods, these are usually dependent on large sets of data, thus making it difficult to apply them in the daily practice of architects and urban designers for evaluating design alternatives. The intention is to compare different measures as indicators of urban walkability based on the study case of the Olympic Village neighbourhood in Vancouver, Canada. Two large-scale walkability indexes were graphically compared with visibility-based measurements and pedestrian movement routes tracked in site. Each method was chosen based on the spatial scale of the variables that compose the measurements: a city-scale walkability index based on the configuration of street grid for the urban whole, a neighbourhood walkability index based on data available at 800m from each building and a pedestrian movement simulation model based on a configurational approach emphasizing visibility and movability in space. Results found similarities between the configurational model and pedestrian movement patterns at the Olympic Village but little agreement between two walkability indexes. Further research is needed to understand why there is little correlation among methods.
A Simulation-based Design Analysis for the Assessment of Indoor Comfort under the Effect of Solar Radiation
Andrea Zani, Henry David Richardson, Alberto Tono, Stefano Schiavon and Edward Arens
One of the drivers of sustainable design is to maximize daylight across the floor plan in order to decrease electric energy consumption and create more productive and healthy working spaces. However, uncontrolled incoming solar radiation can lead to significant visual and thermal comfort issues. In particular, solar radiation landing on occupants can create thermal discomfort that the HVAC system cannot compensate for, thereby causing intolerable conditions for users close to the façade. We aim to present a new climate-based annual framework, based on ASHRAE 55 appendix C (2017), to assess radiant discomfort across a space due to direct solar radiation. The framework is calculated using the hourly effective radiant field (ERF) and delta Mean Radiant Temperature (ΔMRT) across the indoor space. The Radiance-based framework coupled with the proposed Annual Radiation Discomfort metric (ARD) provides designers a robust method to assess the performance of complex fenestration systems (CFS) at reducing potential thermal discomfort caused by incoming shortwave radiation.
Assessing the Performance of UFAD System in an Office Building Located In Various Climate Zones
Roshanak Ashrafi, Mona Azarbayjani, Robert Cox, Benjamin Futrell, Joseph Glass, Amir Zarrabi and Armin Amirazar
The energy performance of Underfloor Air Distribution (UFAD) system is previously investigated in several studies. Energy saving is known to be one of the benefits of UFAD in comparison to other all-air systems; however, there has been some controversy over the performance of UFAD system in each climate. This paper aims to investigate the role of the climatic condition on the energy behavior of the UFAD, compared to the Over Head (OH) air distribution system. To that end, the effects of temperature and humidity on the energy performance of the system are examined in detail. The overall research plan is based on simulating one story of an existing office building in Phoenix with EnergyPlus. The validated model is then used in different ASHRAE climate zones to predict energy consumption in terms of cooling loads, heating loads and fan energy usage for the two systems: UFAD and OH. These comparative analyses have led to a comprehensive understanding of the energy performance of UFAD and OH systems under different climatic conditions. The Results section highlights the overall efficiency of UFAD system, pointing to different percentages of energy saving in each climate. It is found out that UFAD system works best in San Francisco with 26 percent of energy saving and relatively warm climatic conditions, while climates that were too hot or too cold adversely effected the energy saving performance. The lowest percentage of energy saving is 10.31 percent for Duluth in the very cold climate category. The energy saving percentages were then visualized on the map to provide a better spatial understanding of this system’s effectiveness.
Evaluating the Influence of Three Simplifications on Natural Ventilation Rate Simulation (Short Paper)
Yuchen Shi and Xiaofeng Li
Measurement and simulation are two main methods to determine natural ventilation rates in a building. By contrast, the simulation method is widely used in engineering due to its simplicity and convenience. In the practical application of airflow simulation software such as CONTAMW, there exist many simplifications for the actual conditions of simulated buildings. This study focuses on three of the commonly used simplifications and analyses their effects on the simulation results. In addition, for rigorousness, tracer gas decay method is used to verify the reliability of CONTAMW simulation. The conclusions of this study can be used as guidance for airflow simulation software such as CONTAMW.
Black Globe Free Convection Measurement Error Potentials (Short Paper)
Eric Teitelbaum, Jovan Pantelic, Adam Rysanek, Kian Wee Chen and Forrest Meggers
For thermal comfort research, black globes have become the de facto tool for mean radiant temperature, TMRT , measure-ment. They provide a quick, cheap means to survey the ra-diant environment in a space with nearly a century of trials to reassure researchers. However, as more complexity is in-troduced to built environments, particularly by engineering spaces to separate radiative and convective modes of heat transfer for energy efficiency and comfort, we must reassess the relationship of globe readings in the context of their en-vironments. In particular, corrections for globe readings tak-ing wind into account [1, 4] rely on a forced convection heat transfer coefficient. The simulation proposed in this paper demonstrates the influence of free convection on the instru-ment’s readings. Initial studies show that the TMRT and air temperature separations of 2 K could introduce errors equiv-alent to 0.1 m/s of air velocity, providing an additional mech-anism for globe readings to track air temperatures.
Adaptive Occupancy Scheduling: Exploiting Microclimate Variations in Buildings
Max Marschall and Jane Burry
Using natural ventilation instead of mechanical building systems to regulate indoor climate can reduce energy consumption while increasing human well-being. The feasibility of natural ventilation depends on outdoor climate conditions as well as the physical and architectural properties of a building. Based on the observation that institutional buildings are rarely occupied to full capacity, this paper proposes a building operation paradigm aimed at increasing the feasibility of natural ventilation. We introduce the concept of adaptive occupancy scheduling, a prescriptive system that allocates occupants in real time to populate only the most environmentally suitable spaces at all times. We exemplify this paradigm in a school design study, in which a fixed room schedule is replaced by a sensor network that assigns classes to classrooms with appropriate microclimatic conditions on-the-go. Our initial results indicate that a higher local architectural diversity generally increases comfort in free-running mode.
Toward a Multi-Level and Multi-Paradigm Platform for Building Occupant Simulation
Davide Schaumann, Seonghyeon Moon, Muhammad Usman, Rhys Goldstein, Simon Breslav, Azam Khan, Petros Faloutsos, and Mubbasir Kapadia
In recent years, simulation has been used to investigate building-occupant relations while focusing on pedestrian movement, day-to-day occupancy, and energy use. Most of these efforts employ discrete-time simulation, where building and occupant properties are constantly updated at fixed time steps to reflect building and occupant dynam-ics. Real-world occupant behavior, however, involves a va-riety of decision-making patterns that unfold over different time scales and are often triggered by discrete events rather than gradual change. In working toward a platform sup-porting the full range of human activities in buildings, we embed a discrete-time occupant movement simulator called SteerSuite within a general-purpose discrete-event simula-tion framework called SyDEVS. With preexisting SteerSuite functions providing low-level steering behavior, and newly implemented SyDEVS nodes providing high-level planning behavior, our prototype represents a multi-level and multi-paradigm approach to occupant simulation for building de-sign applications.
Multi-Constrained Authoring of Occupant Behavior Narratives in Architectural Design
Xun Zhang, Davide Schaumann, Brandon Haworth, Petros Faloutsos, and Mubbasir Kapadia
Building-Information Modeling (BIM) tools provide static representations of built environments, disjointed from the expected behaviors of their future inhabitants. Current ap-proaches for simulating buildings in use can be categorized as building-centric, where occupancy distributions are speci-fied, behavior-centric, where multi-agent behaviors are mod-eled, or occupant-centric, where occupants behave based on their individual motivations. In this paper, we combine these methods into an integrated framework to author narratives that satisfy multi-level time-varying constraints, such as (a) building-level occupancy specifications, (b) zone-level behav-ior distributions, and (c) occupant-level motivations. Such in-formation is encoded into customizable templates associated with BIM models. A case study highlights the ability of this approach to seamlessly author behavior narratives that can be used for visualizing, analyzing and communicating how buildings may be used by their future inhabitants.
Including Occupant Behavior in Building Simulation: Comparison of a Deterministic vs. a Stochastic Approach (Short Paper)
Max Marschall, Farhang Tahmasebi and Jane Burry
Data capture and analysis are transforming entire industries, enabling novel solutions developed from a numeric evaluation of real-world phenomena. This generally relies on gathering data on physical conditions and users to create accurate, predictive models and provide customized solutions. Increasingly, data-driven approaches are also becoming a part of architectural design, with the goal of creating user-centric and sustainable buildings. However, while simulation software can accurately model deterministic physical effects, it is still difficult to incorporate stochastic effects related to human factors. This paper analyses one aspect of occupant behavior – window operation – to give designers an intuition of the impact of occupant behavior and associated modelling approaches on building performance. To this end, behavioral patterns observed in a previous field study were incorporated into a dynamic energy simulation and compared to a deterministically modelled baseline. While the stochastic models appear to better capture the dynamic and probabilistic nature of occupants’ actions, the present study highlights the extent to which the assumption with regard to occupant behavior can influence the simulation-assisted performance based design process. The paper also makes suggestions as to how to interpret such simulation results in a way that quantifies the intrinsic uncertainty in stochastic models. We argue that increased data capture and analysis of building inhabitants could lead to a better understanding of their behavior, thereby affecting the decision-making process in favor of a more sustainable and responsive architecture.
Modeling Praxis: the Case of the Living Building Challenge at Georgia Tech
Todd Mowinski, Alissa Kingsley, Joshua Brooks
This session will feature simulation and monitoring applications developed at Georgia Tech specifically for the Kendeda Building for Innovative Design, the Southeast’s first fully operational Living Building, located in the heart of GT’s campus. Members of the design and engineering team will discuss approaches to building systems simulation, and provide commentary on the new Net+ Water Scenario Explorer, a cutting edge predictive water management app.
Rotoform - Realization 0f Hollow Construction Elements Through Roto-Forming with Hyper-Elastic Membrane Formwork
Oliver Tessmann and Samim Mehdizadeh
The paper presents a digital process chain for modeling, simulating and fabricating rotationally molded, individualized hollow concrete components using material-efficient and geometrically flexible formwork systems made from hyperelastic membranes. The hollow concrete components are to be used as prefabricated components for architectural constructions. The inner cavity can be efficient in different ways: To save weight and material, for subsequent filling with other materials (insulating, climate regulating, water heating circulation etc.) or as permanent formwork for solid, reinforced structural components that are poured with concrete. Rotoforming concrete significantly reduces the hydrostatic pressure within a formwork and therefore unlocks completely new possibilities for material-efficient and geometrically flexible formwork systems.
Environmentally Informed Robotic-Aided Fabrication
Carmen Cristiana Matiz, Heather “Brick” McMenomy and Elif Erdine
The research presented in this paper addresses the integration of thermal performance with robotic toolpath generation for nomadic settlements. It is part of a larger study that describes the development of a material system and a remote on-site fabrication strategy for African nomadic dwellings using unprocessed locally sourced materials in hot arid environments. Research methods include the employment of computational design and robotic fabrication techniques to facilitate the development of improved housing conditions. Through the analysis of existing traditional earthen construction strategies, the aim is to develop a novel approach to robotic fabrication of unfired earthen envelopes by incorporating thermal performance simulation in the robotic motion path generation. The use of robot-aided fabrication eliminates the need for complicated prefabricated moulds, achieving improved environmental performance with reduced material usage. Taking into consideration the material properties and associated drying times, a layer sequencing strategy is introduced to diminish the possible errors and collapse that occur during the fabrication process. Two types of layers are identified in relation to their position within the envelope’s structure and are optimized for increasing thermal lag, and respectively, self-shading. The contribution of the research is a robot-aided fabrication-aware design method for generating complex thermally performant earthen envelopes realized by overlaying continuous layers using simple toolpath geometries.
Curved-Crease Folding and Robotic Incremental Sheet Forming in Design and Fabrication
Elif Erdine, Antiopi Koronaki, Alican Sungur, Angel Fernando Lara Moreira, Alvaro Lopez Rodriguez, George Jeronimidis and Michael Weinstock
The research presented in this paper addresses the themes of generative design, material computation, large-scale fabrication and assembly technologies by incorporating two research fields, Curved Folding and Robotically Aided Single Point Incremental Sheet Forming (RA-SPIF) of sheet metal panels. The design and construction of a large-scale prototype made of complex panels of sheet metal serves as the case study for the proposed methodology. Global geometry panelisation is implemented through a multiple-criteria Evolutionary Algorithm to establish an equal subdivision approximation of the initial geometry. The mathematical principles of Curved Folding are applied on the resulting mesh geometry. Iterative FEA of the component assembly defines areas where Incremental Sheet Forming needs to be applied to the curved folded components. Selected panels are formed with RA-SPIF to enhance the structure’s performance for wind loading. The primary contribution of the research is the demonstration of a methodology that integrates the precise computation of curved folded geometries and the employment of FEA as a design driver for the application of incremental sheet forming towards the geometrical and material stiffening of sheet material.
Structural Performance of Semi-regular Topological Interlocking Assemblies
Michael Weizmann, Oded Amir and Yasha Jacob Grobman
The principle of Topological Interlocking (TI) suggests using discrete blocks for assembling self-supporting structures. Several studies showed high quality Finite Element analyses for simple types of interlocking assemblies, composed of either tetrahedral or cubic blocks. Recent research has revealed that there are many more types of blocks suitable for assembling interlocking structures. The presented paper is part of an ongoing research on TI in architecture. The current stage of the research focuses on the correlation between the geometry of TI blocks and the structural performance of the whole assembly. The paper presents the results of a series of numerical analyses of various TI-based structures, revealing interesting relations between geometrical parameters and the force-deformation response of TI assemblies.
Data-driven Material System of Graded Concrete Structures
Elisabeth Riederer and Anuradha Suryavanshi
This paper describes the development and results of strategies for improving the environmental and economic aspects of concrete structures. As (marine) sand suitable for concrete construction is becoming increasingly scarce, concrete construction is becoming consequently increasingly expensive. Thus, the need for an alternative building material arises. The inclusion of PET as a replacement for sand and making use of 3D printing as a fabrication method is examined, and the effect on structural performance will be examined further by using a gradient of plastic content. Research methods include the employment of computational design and 3D-printing fabrication tools that incorporate geometric and material constraints tested one-to-one on physical samples. Due to the fact that the material composite functions best in compression, a shell is chosen as a specimen for computational analysis. Based on the global shell´s structural limitations of concrete the effect of local variation in material composition is analysed and evaluated. The goal of the present research is to illustrate a design approach for similar material systems with the aim of improving material properties for use in more environmentally tolerable, efficient and economical building, while testing geometric and material constraints as well as using low cost fabrication methods.
Modularizing Tensegrity Systems: An Approach to Controllable Independent Modules
Arian Saeedfar and Paniz Farrokhsiar
Tensegrity structures are among the most efficient types of structures. Since the introduction of tensegrity structures by Richard Buckminster Fuller, there has been a lot of interest from architects and engineers to further study tensegrity structures and expand their use cases and application. Roadblocks such as complexity of simulation and unpredictability of their behavior, as well as their nonlinear reaction to side forces, have made it difficult to use them routinely in the realms of architecture and engineering. Many research projects have studied the dynamics of tensegrity structures and possibilities for expanding them beyond a single module. While most of the previous research contributes to the control systems for interdependent tensegrity modules, limited research has been performed on simple ways to expand the tensegrity systems using independent modules or blocks. The objective of this paper is to introduce a new method for easy expansion of tensegrity structures using independent modules. Leveraging experimental methods, a new component called “node” is introduced to the tensegrity module to provide the possibility for the interaction of two adjacent modules. Simple grids of the new expandable modules are simulated to verify the stability of newly designed systems and identify the key variables for controlling interdependent modules. Factors such as tension, displacement, and utilization are also analyzed in the simulations.
A Framework for Cost-Optimal Zero-Energy Lightweight Construction (Short Paper)
Mohamed Amer and Shady Attia
During the last decade, several roof extensions took place in the European cities with the purpose to increase the height of existing buildings using timber as a lightweight material. However, building regulations and green codes do not usually guarantee the achievement of multi-objective and highly performance roof extensions. Accordingly, this research aims to develop a state of the art framework to achieve cost-optimal zero-energy for timber construction, specifically when building on rooftops. Through a simulated and calibrated passive house model, the boundary conditions of the study have been identified and further parametric simulation and optimization have been carried out. This research aims at linking scientific research with practice. The framework provides a fast track measurement that provides a solutions space for building engineers who are in charge of decision making on the design and construction process. Best practices of roof construction could be achieved in terms of cost and energy, giving a vast potential for a complete and deep renovation, and, therefore, reducing the overall ecological footprint on the city level.
An Automated Framework Creating Parametric BIM from GIS Data to Support Design Decisions
Chengde Wu, Saied Zarrinmehr, Mohammad Rahmani Asl and Mark J. Clayton
GIS has been primarily used for urban scale projects. On the other hand, BIM has been mainly used for building scale projects. Understanding surrounding site context is essential in building design. Thus, architects often utilize GIS data to build 3D digital and physical models of the surrounding urban/natural context to help them make better design decisions. The primary challenge of building 3D models from GIS data is that the modeling process requires tremendous load of manual work due to the fact that the data scheme used in GIS is not directly compatible with the data scheme used in BIM. In this research, we analyzed the difference between GIS and BIM data schemes, formulated a data mapping protocol, devised algorithms to correctly convert 2D GIS data to 3D geometries in BIM, programed a software prototype that can automatically convert a model from GIS to BIM, and conducted pilot tests of two different cities to verify the validity of the overall framework. This automated system greatly reduced the modeling time, manual workload, and potential manmade errors. It is expected to facilitate architects in rapidly creating 3D models and study the surrounding urban/natural context.
Digital Energy Performance Signature Extensible Markup Language (DEPSxml): Towards a New Characterization Framework for Sharing Simulation and Measured Data on Building Design and Energy Performance
Justin McCarty and Adam Rysanek
This paper introduces a new filetype that has the potential to improve data analytics in the building sector. The aim of the paper is to explore the general logic and hierarchy of the file type, explore the mechanism in which it would transmit data, and define initial user groups and the process by which they would use the file and server system. The filetype utilizes a popular green building filetype (gbXML) as a base schema. The manner in which the base schema is expanded upon is explored in the paper to clarify how a live link to a building’s automation system and utility network may be established in an Extensible Markup Language (XML) file format. The last section of the paper contributes several potential uses for the new filetype that will be put into place during the beta phase.
From Optimization to Performance-Informed Design
Thomas Wortmann and Thomas Schroepfer
This paper introduces performance-informed design space exploration (DSE) to question the relationship between explicit, quantitative optimization problems and “wicked”, co-evolving architectural design problems and to support the reframing of architectural design optimization as a medium for reflection. The paper proposes selection, refinement, and understanding as key aspects of performance-informed DSE and surveys current approaches to performance-informed DSE: (1) Clustering and Pareto-based optimization support selection by reducing large numbers of parametric design candidates into smaller and more meaningful sets of choices. (2) Surrogate modelling supports refinement by approximating time-intensive simulations in real-time, which is important for interactivity. (3) Multi-variate visualizations and statistical analyses support understanding by providing insights into characteristics of design spaces and fitness landscapes. Finally, the paper discusses a novel tool for visual and interactive, performance-informed DSE, Performance Explorer. Performance Explorer combines the real-time feedback afforded by surrogate models with a multi-variate visualization of fitness landscapes. A user test of Performance Explorer uncovered several performance-informed DSE strategies followed by the participants. Consisting of different combinations of selection, refinement, and understanding, these strategies illustrate and—to some extent—validate the proposed framework for performance-informed DSE.
Linear and Classification Learner models for Building Energy Predictions and Predicting Saving Estimations
Kevin Eaton, Nabil Nassif, Pyrian Rai and Alexander Rodrigues
The need for creating building systems with smart systems is growing. Saving energy in buildings is both important in aiding the environment and saving money for the companies and organizations who run those buildings. Most buildings are now equipped with technology to produce accurate electrical outputs that can be used for improving the accuracy of energy models. This paper discusses typical data-based building energy models and proposes new improvements by utilizing a classification learner. Estimating sub-hourly and hourly electric energy consumptions are discussed using four different data-based models. The first model is a linear fit model using one regressor, the second is a linear change point fit using one regressor, and the third model is a two regressor model using a linear fit. The fourth model is a proposed Classification Learning model using three regressors. Two different types of data were collected: simulation and actual data. There are four buildings total: two with simulation and two with actual data. The results show that the proposed Classification Fine KNN model can provide accurate predictions for the data as compared to traditional linear modeling techniques. These models are then utilized to calculate saving percentage, which is then compared to the actual percentage.
From Drawing Shapes to Scripting Shapes: Architectural Theory Mediated by Shape Machine
Heather Ligler and Athanassios Economou
The shape grammar formalism has offered a visual, rule-based framework for interpreting architectural languages for over forty years. However, the ability to implement grammars within a technology that allows for direct engagement with shape rules and productions so that they can be dynamically simulated, shared, understood, modified, and brought into a more active theoretical dialogue is only partially achieved. The work here asks how a new technology that allows shape rules to be implemented by drawing shapes to specify scripts instead of writing code can reinvigorate shape computation to advance formal analysis and synthesis in architectural research. More precisely, a case study to implement an analog grammar on John Portman’s domestic language with a new shape grammar interpreter, the Shape Machine, is presented to take on this question. The results are illustrated as a visual catalog of sample designs generated in the software. The results suggest further insights on Portman’s language of the house prompted by the machine-based specification.
Interpreting Non-flat Surfaces for Walkability Analysis
Mathew Schwartz and Subhajit Das
Through laser scanning, GIS data, new manufacturing methods, and complex designs, analysis of terrain in relation to human mobility is becoming ever more necessary. While standards for wheelchair ramps exist, they rarely show the entire picture, nor do they account for surface variation beyond a single axis. Although graph creation techniques in CAD exist for flat terrain, directional edge weights accounting for this variation are lacking. In this paper, a summary of research from both biomechanics and architecture in relation to surface walkability is presented, followed by a review of creation methods for a searchable graph representing an environment in CAD. A novel graph creation method that can respond to variations in surface height for walkability analysis is presented, where the edge weights of the graph are based on surface condition of parent-child height variations.
Generating Acoustic Diffuser Arrays with Shape Grammars
Jonathan Dessi-Olive and Timothy Hsu
This paper presents research on a rule-based approach to designing creative acoustic diffuser arrays. A shape grammar-influenced design method is specified that uses shape rules to recursively design arrays of quadratic residue diffusers (QRD) in ways that are neither mechanical nor deterministic.
A Unified Framework for Optimizing the Performance of a Kinetic Façade
Ok-Kyun Im, Kyoung-Hee Kim, Armin Amirazar and Churlzu Lim
A noble kinetic façade system, Oculi Kinetic Façade System (OKFS) was developed to balance solar heat gain, daylighting, and user satisfaction. The study focused on a dynamic control scheme that incorporates simulation data to determine optimal angles of the OKFS for given hours. This research considered daylighting and solar irradiance as the performance metrics. In order to reflect two metrics, we employed a min-max normalization method with a weighting factor in the proposed scheme. The weighting factor is determined by the performance of OKFS at the given time. The implementation of the control scheme is demonstrated via a case study, where simulation data was generated through the Grasshopper Diva 4.0. The result indicated that the optimal control of the rotational angle of OKFS can improve the daylight performance up to around 10%. It is expected that the findings from this study can contribute to developing a systematic optimization model of a kinetic façade system as well as an evaluation scheme for the performance of kinetic façade system.