Air Cleaning Technologies & Intelligent Controls for IAQ & Energy Efficiency

Air Cleaning Technologies & Intelligent Controls for IAQ & Energy Efficiency

A SyracuseCoE Research & Technology Forum

Wednesday, March 29th – 3:00 to 4:30 pm

Tour of BEST Lab and networking reception to follow

Register: In-Person | Virtual

FORUM: This SyracuseCoE Research & Technology Forum will highlight the findings from a joint research project between Syracuse University and Honeywell.

The objectives of the study included 1) to develop a comprehensive test method for evaluating the effectiveness of various air cleaning technologies for various indoor pollutants including volatile organic compounds, particulates, and viruses, 2) to develop advanced control methods and algorithms for HVAC system controls, 3) to evaluate the impact of intelligent air cleaning and ventilation control strategies on IAQ, occupant satisfaction, comfort, and performance.

MODERATORS: Professors Jianshun “Jensen” Zhang, Bing Dong and Dacheng Ren.

TOUR AND NETWORKING: There will be networking reception and optional tour after the forum of the Built Environment Science and Technology Laboratory (BEST Lab), led by Professor Bing Dong. This is a new laboratory at SyracuseCoE specializing in IAQ, occupant behavior and intelligent control research and development.

Presentations:

Performance of various air cleaning technologies: test method and evaluation results for VOCs and particulates

Zhenlei Liu, Ph. D. Candidate and Research Assistant, Department of Mechanical and Aerospace Engineering, Syracuse

Zhenlei Liu’s focus is on building energy saving, indoor air quality and indoor chemistry. His research interests lie in studying VOC emissions from building materials and human activities. In his most recent study, he conducted a series of laboratory chamber tests on evaluating ten portable air cleaners in removing particles, VOCs, and viruses, as well as the by-products generated by the air cleaners, including ozone, hydroxyl radicals, and VOCs. Zhenlei’s other recent research includes studies on a similarity approach to estimate partition coefficient of a building material and studies on indoor chemistry of VOCs secondary emissions.

Faculty Advisor: Jianshun “Jensen” Zhang, BEESLab, Mechanical and Aerospace Engineering, Syracuse University

Effectiveness of various air cleaning technologies for removing and disinfecting viruses

Eloise Parry-Nweye, Ph.D. Candidate, Department of Biomedical and Chemical Engineering, Syracuse University

Eloise Parry-Nweye’s research interests are in understanding the synergistic effects of environmental factors and material properties on virus persistence. In her most recent study, she investigated the humidity-dependency of virus survival on porous materials. Previously, she established effective sampling methods for aerosolized virus which she deployed towards evaluating the efficacy of varied air cleaning technologies in removing infectious virus from air. In addition, she studied the interaction of TVOCs with aerosolized virus under ambient conditions, as trace VOCs are inevitably emitted from building materials into indoor air. Her experiments have been conducted in a full-scale aerobiology chamber in the Building Energy and Environmental Systems Laboratory (BEESL) which simulates a realistic indoor environment.

Faculty Advisor: Dacheng Ren, Biomedical and Chemical Engineering, Syracuse University

Model predictive control to save energy while improving good IAQ

Xuezheng Wang, Ph. D. Student, Department of Mechanical and Aerospace Engineering, Syracuse University

Xuezheng Wang’s focus is on building energy saving, indoor environmental quality, and optimal control. His research interests lie in studying predictive control of HVAC systems for a balance of energy consumption and indoor environmental quality. In his most recent study, he developed a control-oriented, physics-informed neural network of indoor dynamics and hierarchical predictive control strategies for HVAC systems. Xuezheng’s other recent research includes reinforcement learning for optimal building control.

Faculty Advisor: Bing Dong, BESTLab, Mechanical and Aerospace Engineering, Syracuse University

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