Sustainable & Resilient Building Design
Buildings are major consumers of energy and material resources and can be vulnerable to natural and man-made hazards. Poor performance of a building in a number of areas, like structural integrity and energy use, can result in disruption to the regular functionality of the building and even communities. Bringing buildings back to full operation after a disruptive event can result in additional resource consumption and life cycle impacts. Making building more material, energy, and water efficient can, in turn, make them more resilient, and on-site energy generation, water collection, and water treatment may ensure continuous functionality during disruptions to the grid. This research area focuses on evaluating the sustainability and resilience of buildings during the design phase but also analyzes impacts of existing buildings and rating systems.
Sustainability & Resilience Metrics
There is some consensus on the factors influencing building resilience and sustainability, and both have been studied individually to inform codes and rating systems; however, little has been done in the quantification and analysis of the two aspects side by side and in regards to buildings. The goal of this research is to define quantitative metrics for characterization of building systems and components and their effect on the sustainability and resilience of the building as a whole. The approach and metrics focus on the early design phase, creating a platform for performance-based design of sustainable and resilient buildings.
Life Cycle Structural Resilience to Natural Hazards
Our approach to the quantification of sustainability and resilience of building designs builds on the typical whole building life cycle assessment approach. While typical building LCA focuses on operational energy use and embodied energy in building materials, our approach also includes earthquake engineering and water treatment methods to expand the scope of the assessment, and consider the structural integrity and water demand of the building.
Building-Scale Water Impacts and Self-Reliance
The diversity of building systems and self-reliance of the building from an energy and water standpoint is also important for the resilience of the building. As part of the development of computational approaches in this regard, and to be able to relate such building characteristics to the life cycle assessment approach, we have extensively studied a local net-zero energy and water building.
Global Perspective on Building Energy Use and Environmental Impacts
This research investigates the relationship between energy use, geographic location, life cycle environmental impacts, and Leadership in Energy and Environmental Design (LEED). The researchers studied worldwide variations in building energy use and associated life cycle impacts in relation to the LEED rating systems. A Building Information Modeling (BIM) of a reference 43,000 ft2 office building was developed and situated in 400 locations worldwide while making relevant changes to the energy model to meet reference codes, such as ASHRAE 90.1. Then life cycle environmental and human health impacts from the buildings’ energy consumption were calculated. The results revealed considerable variations between sites in the U.S. and international locations (ranging from 394 ton CO2 eq to 911 ton CO2 eq, respectively). The variations indicate that location-specific results, when paired with life cycle assessment, can be an effective means to achieve a better understanding of possible adverse environmental impacts as a result of building energy consumption in the context of green building rating systems. Looking at these factors in combination and using a systems approach may allow rating systems like LEED to continue to drive market transformation towards sustainable development, while taking into consideration both energy sources and building efficiency.
Parametric Life Cycle Assessment & Costing
This study explored the use of LCA results of parametrized reference buildings for benchmarking purposes and compared them to real building projects. The building performance is calculated using an automated process of energy modeling, life cycle assessment and costing, and seismic loss assessment. The physical model was based on the Department of Energy (DOE) Medium Office Reference Building and is adjusted using a Python algorithm based on inputs of building shape, length, width, floor-to-floor height, number of stories, and window-to-wall ratio (WWR).
The framework was used to obtain the total life cycle results for a 60-year study period for 4,608 unique design and service scenarios across seven environmental and economic metrics and two locations. Each building was represented by a single circle. As an example, the black circles in the plot below represent a single building design and service combination scenario out of the 4,608 possibilities. Many of the results were so close to each other that the circles formed a visually continuous line, but in fact they were many clustered circles. This clustering indicated that there were many buildings whose design or service decision differences yielded very small differences in the overall results in that metric. Conversely, large gaps between these clusters indicated a major influencing factor splitting the results clusters apart.
The application of the framework on the medium office building used a combination of modeled and average reported data, making it sort of a hybrid approach. Future studies could make more homogenous approach in either full bottom-up modeling of all aspects or top-down assessment based entirely on reported data. The specific scenario analyzed in this case showed a potential for revealing the worst case and best case scenarios in various performance metrics and revealed the influence of individual life cycle stages. Future studies could expand the number of considered materials, constructions, service options and other aspects affecting building performance. Once it is possible to generate more sophisticated building models and design and service options, the presented approach could be used to generate baseline buildings for real building projects.
Hasik, V., Ororbia, M.E., Warn, G.P., Bilec, M.M.* (2019). “Whole Building Life Cycle Environmental Impacts and Costs: A Sensitivity Study of Design and Service Decisions.” Building and Environment, August 2019, 106316 https://doi.org/10.1016/j.buildenv.2019.106316
Hasik, V., Escott, E., Bates, R., Carlisle, S., Faircloth, B., Bilec, M.M.* (2019). “Comparative Whole Building Life Cycle Assessment of Renovation and New Construction.” Building and Environment, 161, 15 August 2019, 106218. https://doi.org/10.1016/j.buildenv.2019.106218
Hasik, V.A., Chhabra, J., Warn, G.P. Bilec, M.M.* (2018). “Review of approaches for integrating loss estimation and environmental life cycle assessment for earthquake damage to buildings.” Engineering Structures, 175(November 2018), 123-137. https://doi.org/10.1016/j.engstruct.2018.08.011
Chhabra, J., Hasik, V., Bilec, M.M., Warn, G.P (2017). “A probabilistic approach for assessing the environmental performance of building designs accounting for natural hazards.” ASCE Journal of Architectural Engineering, 24(1):04017035. https://doi.org/10.1061/(ASCE)AE.1943-5568.0000284
Hasik, V., Anderson, N.E.+, Collinge, W.O., Thiel, C.L., Khanna,V., Wirick, J., Piacentini, R., Landis, A.E., Bilec, M.M.* (2017). “Evaluating the life cycle environmental benefits and tradeoffs of water reuse systems for net-zero buildings.” Environmental Science & Technology, 51(3), 1110-1119. http://dx.doi.org/10.1021/acs.est.6b03879
Al-Ghamdi, S., Bilec, M.M.* (2016). “On-Site Renewable Energy and Green Building Rating Systems: A System-Level Analysis.” Environmental Science & Technology, 50, 4606-4614. http://dx.doi.org/10.1021/acs.est.5b05382
Al-Ghamdi, S., Bilec, M.M.* (2017). “Green Building Rating Systems and Whole-Building LCA: A Comparative Study of the Existing Assessment Tools.” ASCE Journal of Architectural Engineering, 23(1):04016015. http://dx.doi.org/10.1061/(ASCE)AE.1943-5568.0000222