Current Projects
Building Energy Retrofitting
Retrofitting old buildings is a key step towards reducing energy consumption and improving indoor environmental quality. We are working on developing an automated building retrofit planning tool that can generate optimal retrofit plans for any building of interest through generative AI and Machine Learning. This tool will provide predictable outcomes and maximize return on investment (ROI) for the retrofit
Fast Building Energy Modeling
Recent advancements in computer vision techniques provide new opportunities for rapid building geometry modeling. By utilizing tools like drones, LiDAR, thermal imaging, and other remote sensing technologies, buildings can be modeled much faster. The goal of this project is to develop a non-invasive, fast method for creating building energy models by combining these techniques. These energy models can be used to evaluate optimal building retrofitting alternatives.
Thermal Comfort Modeling and Optimization
The objective of this project is to improve thermal comfort and energy efficiency in buildings by coordinating the HVAC setpoints and the operations of personal comfort systems (PCS). Dynamic personal comfort modeling is used to replicate thermal needs of occupants in real-life scenarios. In addition, different control strategies are assessed to explore the tradeoff between thermal comfort and operational energy in buildings.
Resulted publications:
Al Jebaei, H., & Aryal, A. (2022). Quantifying the impact of personal comfort systems on thermal satisfaction and energy consumption in office buildings under different US climates. Energy and Buildings, 274, 112448.
Thermal Energy Storage
The objective of this project is to develop Phase Change Material (PCM) composites that can be installed in buildings to enhance energy efficiency in buildings. This work is running a collaboration with different established faculties from different departments at Texas A&M University. Laboratory work is involved to design and produce energy efficient PCM composites. In addition, laboratory experiments are used to test mechanical properties of PCM composites and simulations are utilized to assess building performances.
Collaborators
Zachry Department of Civil and Environmental Engineering -Texas A&M University
Department of Architecture -Texas A&M University
Funded by: Texas A&M Triads for Transformation (T3) program
Resulted publications:
Jeon, I. K., Azzam, A., Al Jebaei, H., Kim, Y. R., Aryal, A., & Baltazar, J. C. (2023). Effects of alkali-activated slag binder and shape-stabilized phase change material on thermal and mechanical characteristics and environmental impact of cementitious composite for building envelopes. Journal of Building Engineering, 76, 107296.
Jeon, I. K., Azzam, A., Al Jebaei, H., Kim, Y. R., Aryal, A., & Baltazar, J. C. (2023). Effects of shape-stabilized phase change materials in cementitious composites on thermal-mechanical properties and economic benefits. Applied Thermal Engineering, 219, 119444.
Human-Robot interaction in Construction
There is a growing interest in adopting robots in the construction industry to address the issues of declining productivity, labor shortage, and imposed work restrictions due to covid-19. As robots get introduced to the project sites, human-robot interaction becomes an important consideration for wide-scale adoption. The success of deploying robots in the construction industry depends on how well humans collaborate with the robots. This project focused on investigating the perception of various construction industry stakeholders in adopting robots in their projects, and the level of control they feel can be delegated to robots. This project also investigated major factors that impact the decision to use a robot for a particular task. The research used a survey to collect relevant data from various construction industry stakeholders for specific types of robots that were applicable to the construction industry
Funded by: Transportation Consortium of South-Central States (Tran-SET) - Project No. 21COLSU06