<p class="KEYWORDS">Architectural designers are currently faced with many challenges&mdash;technological changes, environmental and economic impacts, necessity to innovate and raise the bar in building performance, and the paradigm shift in architecture with the wider adoption of advanced computational design and fabrication techniques. This paper focuses on innovations in architecture, relationships between scientific research and design, and advanced building technologies. Several research projects are presented, including use of virtual and augmented reality for design, smart facade systems for generating heating/cooling and electricity, and regenerated buildings with improved performance.</p>

This research investigated energy-efficient (EE) retrofit strategies for a historically and culturally significant residential building complex, located in Sarajevo, Bosnia and Herzegovina. The objective was to evaluate existing building performance and propose delicate, EE retrofit strategies while preserving the original design character. The overarching objective was to demonstrate a framework through which historically and culturally significant buildings can be investigated for EE retrofitting. Using original construction drawings and current photographs, a 3D BIM model of a typical residential building was developed for analysis and energy simulations. Next, using Revit and Insight 360 simulations, the building's response to environmental conditions was evaluated. Thermal behavior and moisture resistance performance of typical facade systems were evaluated using WINDOW, THERM, and WUFI simulations. Lastly, a full-building energy model was developed in IES-VE software to simulate full-building performance. Results showed that while the conceptualization of this neighborhood paid careful attention to social and environmental factors and had implemented some of the most advanced passive and active technologies of that time, a typical residential building generally underperformed in all evaluated criteria. The proposed retrofit strategies, focusing on improving the building enclosure and implementation of EE mechanical systems, achieved 53% energy-use reduction and elimination of fossil-fuel energy sources.

This research investigated renovation considerations and design strategies for post-pandemic, hybrid office environment within an academic institution. The focus was on two case-study office spaces that are part of the same organization at the University of Utah, where the existing physical space was insufficient for future growth and non-functional for its novel, hybrid work mode structure. The objective was to evaluate the physical conditions of the existing office spaces, to investigate the employees’ working patterns and office culture, and to propose renovation strategies that would meet both the current and the projected future needs that support a hybrid work structure. The study was based on mixed-mode research methods, which included qualitative and quantitative methods. Qualitative methods included archival and empirical research of the existing office space conditions, as well as users’ input through online survey and focus group interviews. Using the latest, as-built construction drawings and current state photographs, 3D BIM models of each of the two office wings were developed, inclusive of their structural elements, partition walls, existing lighting fixture locations and specific furniture arrangements. These models were then used for egress, circulation, daylighting, and existing space planning analysis. Literature review was also conducted, identifying rising trends and design considerations for hybrid office workflow. Surveys and focus group interviews were conducted with current employees of the two offices to evaluate work patterns and space needs through user insight. Meanwhile, quantitative methods included quantitative analysis of the survey and focus group interview results, computational modeling, and visualization of the existing and proposed design strategies, as well as a review and validation of final design’s egress and accessibility compliance. Through several design option iterations, these results were used to provide space planning strategies and recommendations that meet the specific needs of these two office spaces. The final design, which considered users’ input regarding team dynamics, work schedules, and specific space and function needs, achieved a significant improvement in balances between team and individual space functions, private and public circulation, access to daylight and accessibility, while respecting the existing wall partitions, egress paths and occupancy counts. Moreover, the design solutions provided inclusive, comfortable, and functional spaces that catered to the specific work culture and individualized needs of employees. While this research focused on two specific case-studies, results demonstrate that through a user-integrated approach, significant improvements can be achieved to provide well-functioning spaces and a more comfortable and inclusive working environment. Additionally, the presented process that focuses on user-input and participation in the renovation design process can be applied to other existing, traditionally structured office spaces when transitioning to a hybrid office structure.

Despite immense efforts to ensure equitable COVID-19 vaccination access, many global communities had remained marginalized without access to vaccines or with limited supplies and accessibility to vaccines. In the United States, inequalities in vaccination access were and continue to be reflected across demographics of race, income, and geographic location, where minorities and low-income populations recorded lower rates of vaccination. Using a combination of QGIS, R Studio, SPSS, and GeoDa software to code and analyze publicly available data for Milwaukee, historical patterns of systemic exclusion, specifically redlining, were compared to current-day access to healthcare as reflected by vaccination rates. Spatial and statistical analysis showed a strong correlation between historically marginalized neighborhoods and low vaccination rates despite vaccines being federally funded and available to all US residents. Through this quantitative framework, other US cities can be similarly studied for the impacts of historic redlining on social equity and accessibility issues beyond healthcare access.

Linear regression analysis is one the most common methods for weather-normalizing energy data, where energy versus degree-days is plotted, quantifying the impacts of outside temperature on buildings’ energy use. However, this approach solely considers dry-bulb temperature, while other climate variables are ignored. In addition, depending on buildings’ internal loads, weather impact can be less influential, making the linear regression method not applicable for energy data normalization in internally driven buildings (such as research laboratory buildings, healthcare facilities, etc.). In this study, several existing buildings from different categories, all located on the University of Massachusetts Amherst campus and exposed to the same weather conditions in a heating-dominated climate, were analyzed. For all cases, regression of monthly steam use on heating degree-days and floor-area normalized steam data were used, investigating applicability of the former when the latter changes. It was found that internal loads can skew steam consumption, depending on the building functionality, making the effect of degree-days negligible. For laboratory-type buildings, besides heating and domestic hot water production, steam is also used for scientific experiments. Here, daily occupancy percentage, even during weekends and holidays, was higher than that of other buildings, indicating the intensity of scientific experiments performed. This significantly impacted steam consumption, resulting in higher floor-area-normalized steam usage. In these cases, steam use did not provide an outstanding correlation to heating degree-days. Whereas, for cases with other functionality-types and lower floor-area normalized steam, coefficients of determination in regressions were high. This study concludes that even for buildings located in the same climate, depending on how building functionality and occupancy schedule influence floor-area normalized steam use, multivariate linear regression can provide more accurate analysis, rather than simple linear regression of steam on heating degree-days.