<p>  </p> <p>Recent developments in radiative cooling paints have shown significant promise towards commercialization of the technology. Therefore, questions have been asked as to how the durability of these paints could be evaluated and improved, as well as how these paints could impact energy use and global climate change. In this work, a paint formulation was developed using nanoplatelet hBN pigments with an MP-101 binder from SDC Technologies, Inc. This formulation shows similar reflective properties to that of an hBN acrylic formulation (97.5% and 97.9% reflectance, respectively) while boosting a water droplet contact angle of as much as 120°, proving hydrophobicity and therefore self-cleaning properties. Additionally, a comprehensive study was conducted to understand the potential impact of the radiative cooling paints on the changing global climate. Three potential impacts of the paint were discussed, including capture and utilization of CO2 into the CaCO3 paint, the reduction of HVAC usage on buildings painted with the RC paints, and net cooling of the earth due to the solar reflection and thermal emission of the paint into deep space. It was discovered that all three parts had a positive impact on the global climate, regardless of which US climate zone the representative building was in. Additionally, it was found that the paints could reduce as much as an equivalent 539 lbs CO2eq from the atmosphere for each m2 of the paint applied.</p>

<p dir="ltr">Building Information Modeling (BIM) supports engineering and performance analysis for buildings and civil infrastructure from the initial design stage. BIM offers engineers access to building and infrastructure objects, along with their associated data, which can be utilized across various platforms to develop analytical models. However, the interoperability between BIM and analytical models is still limited and challenging. One such limitation and challenge is in the interoperability between BIM and Building Energy Modeling (BEM). Despite the fact that interoperability of geometry and material information between BIM and BEM has been extensively investigated, the interoperability of heating, ventilation, and air conditioning (HVAC) information, which is a crucial part in BEM, was underinvestigated. Another limitation is that the shared objects frequently lose their identification across different models during the processes of their creation, design iterations, and model transformation. In addition, current building and civil infrastructure projects mainly rely on Portable Document Format (PDF) plans as the official deliverables and documents to be stored, communicated, and transferred among different stakeholders. The transition from 2D PDF plans to 3D BIM remains challenging because manually creating a BIM instance model from 2D drawings can be laborious, time-intensive, and susceptible to errors.</p><p dir="ltr">To address these gaps, this dissertational research introduces new Industry Foundation Classes (IFC)-based algorithmic methods that utilize the state-of-the-art Data-driven Reverse Engineering Algorithm Development (D-READ) method and the invariant signatures of architecture, engineering, and construction (AEC) objects to (1) develop algorithms that can extract the information from 2D PDF drawings and reconstruct the 3D semantically segmented and enriched BIM instance models, (2) develop object mapping algorithms for interfacing BIM and analytical models (e.g., BEM, structural analysis models, etc.) by automatically mapping building objects, and (3) iteratively develop the HVAC information transformation algorithm between BIM and BEM. Following the proposed methods, algorithms were developed to (1) semi-automate the creation of semantically segmented and enriched 3D IFC-based bridge BIM instance models using 2D PDF bridge plans, (2) map space objects between BIM instance models and BEM (OpenStudio model) based on their invariant signatures, and (3) transform HVAC objects from IFC-based BIM instance models to BEM with all the necessary information for energy simulation, using (1) PDF drawings for 12 bridges located in various parts of Indiana, (2) a 2-story duplex apartment building, and (3) a 2-story office building model and a 2-story residential building model, respectively.</p><p dir="ltr">The developed algorithms were tested on three cases: (1) the PDF information extraction algorithm was tested on six bridges, which achieved 97.7% precision and 94.4% recall. In addition, it decreased the time required to create bridge BIM instance models by 94.9% compared to the manual approach; (2) the object mapping algorithm was evaluated using a 4-story office building model containing 82 spaces. The results demonstrated that the algorithm attained 90% precision and 90% recall in mapping space objects. Additionally, a 4.88% improvement in the accuracy of energy simulation results was observed when compared to simulations without space mapping; (3) the HVAC transformation algorithm was tested on two models with distinct HVAC systems: a 4-story office building model featuring a boiler radiator system and a 2-story clinic building featuring a VAV system. The algorithm achieved transformation accuracies of 97.5% and 98.7%, respectively, compared to manually created evaluation models in OpenStudio. Additionally, the algorithm-generated models demonstrated satisfactory performance with regard to precision, with less than 9.6% error in total annual energy consumption compared to the evaluation models.</p><p dir="ltr">This dissertational research introduces a new IFC-based approach to fill the forementioned research gaps in BIM interoperability for buildings and civil infrastructures. It facilitates improved accessibility compared to a proprietary workflow and will contribute to filling informational gaps (1) between 3D BIM and 2D PDF drawings, and (2) between BIM and analytical models. It builds a solid foundation for achieving (1) automated BIM reconstruction using 2D plans, and (2) smooth, accurate, and fully-automated HVAC objects transformation between BIM and BEM, for complete BIM-BEM interoperability. The proposed approach can also be leveraged to further expand BIM interoperability support by providing a novel data-driven approach for building and civil infrastructure projects.</p>

<p>The construction industry contributes significantly to the GDP of the United States, attributing to its growth at an unprecedented rate. Efficient planning on all stages of construction is the only way to combat dynamic obstructions and deliver projects on time. The first element involved in the planning phase deals with the layout of the Construction Site. It significantly regulates the pace at which construction operations function and directly affects the time, cost, and safety linked to the successful delivery of the target project. Hence, it is paramount to ensure that every component of the construction site maneuvers with the utmost productivity. One such equipment that occupies significant attention while carrying out the CSLP process is Tower Crane. Tower crane optimization is pivotal to ensure proper lifting and handling of materials, and warrant conflict-free work zones. This research, therefore, aims to optimize its position by maximizing the lift ability. To achieve the goals, Generative Design- a paradigm that integrates the constructive features of mathematical and visual optimization techniques, is used to develop a relatively comprehensible prototype. The first part of the research, thus, utilized Generative Design on two construction sites- one from the United States and one from India. After implementing the visual programming algorithm, an improvement of 40% was warranted in the lift score. A pool of potential alternatives was explored and supplemented by the trade-off illustrations. The concept of trade-off was substantiated by allowing a framework for prioritization of lift cycles, and facilitating a holistic decision-making process. To evaluate the usability, 12 participants were chosen based on their previous experience with tower crane operations. The participants witnessed a live demonstration of the algorithm, answered a Likert scale questionnaire, and appeared for an open-ended interview to provide feedback about the proposed Generative Design technique. After carrying out narrative analysis for the usability aspect- it has been unanimously observed that the technique has extreme efficiency of usage and can evidently prevent the occurrence of errors. The study concludes by providing recommendations to augment the significance and usability of Generative Design for tower crane position optimization. </p><br>

<p>This dissertation focuses on the creation of a paradigm shift in building innovation. Challenges in achieving building energy-efficiency at scale highlight the complexity of the building performance problem, which is embedded with social, cultural, physical, environmental, and economic factors. Traditional approaches to building design have difficulty accounting for these multi-faceted variables and related longitudinal barriers and intangible impacts. Firstly, key stakeholders and their economic constraints change throughout time, and this variability is not traditionally considered upfront or addressed throughout a building’s operation. Secondly, buildings have social, cultural, environmental and economic implications that are difficult to quantify and evaluate against strictly functional design objectives. Therefore, current deeply technical and often system-specific building design strategies could benefit from whole-building solutions that account for this complexity and enable a paradigm shift in design toward human-centered outcomes (i.e., well-being, health, financial sustainability) and effective (i.e., equitable and sustainable) buildings. </p> <p>To drive this shift, an impact-based innovation framework was employed to pursue system-level and ecosystem-level strategies to optimize longitudinal building value assessment and distribution. First, a grounded theory study was pursued which identified gaps in current design practice that miss underlying building subsystem interactions which influence building performance. A system-level taxonomy of the building was then defined, linking identified sub-system synergies to functional, emotional and social building benefits for inhabitants. Then, an exploratory mixed-methods study was pursued, yielding a longitudinal building value framework that helps characterize key stakeholders, building design choices, and shared efficacy metrics. Building on these inputs, a multi-stakeholder, longitudinal building value assessment model was developed. The model was tested on two residential building development scenarios, highlighting its ability to capture the true impact of buildings on affected stakeholders over time in terms of tangible and intangible building costs and benefits. Finally, business model innovation concepts were employed to identify specific changes in stakeholder value delivery and capture strategies that could redistribute building costs and benefits over time, and thereby facilitate a shift in the paradigm of design and value capture in the residential building industry. </p>