A Detailed and Systematic Investigation of Personal Ventilation Systems

This research investigates the use of personal ventilation (PV) in a typical office space as a means of contaminant removal from ones breathing zone (BZ). For this work, a validated computational model was developed and used for PV assessment under different scenarios. Experimental data of Khalifa et al. (2009), Ito (2007) and Rim et al. (2009) were used to validate a computational model that is capable of simulating indoor chemical reactions with excellent agreement compared with the experiments. Through the validation process, various computational parameters were determined to be significant for producing accurate results. Grid resolution, geometry, far field BCs, turbulence model and radiation were shown to impact the solutions accuracy and care must be taken. However, it was found that adding complex, realistic features, such as unsteady breathing or sweating, does not improve the accuracy of the inhaled air quality results of the solution. With this knowledge, the benefits of two PV nozzles, a conventional round nozzle and a novel low-mixing Co-flow nozzle, were investigated for an array of scenarios including: non-reacting indoor sources, different office and PV configurations and indoor surface and volumetric reactions. Specifically, the use of PV to remove reaction products of the oxidation by Ozone of Squalene and D-Limonene were analyzed and compared to a conventional ventilation system. The Co-flow nozzle was shown to exhibit superior performance and robustness over a single jet PV system and both PV systems improved air quality in the BZ over conventional systems. It was found that well mixed behavior is not exhibited especially with large velocity and concentration gradients that are developed by the use of PV and/or when indoor sources or chemical reactions are present

A review of advanced air distribution methods - theory, practice, limitations and solutions

Ventilation and air distribution methods are important for indoor thermal environments and air quality. Effective distribution of airflow for indoor built environments with the aim of simultaneously offsetting thermal and ventilation loads in an energy efficient manner has been the research focus in the past several decades. Based on airflow characteristics, ventilation methods can be categorized as fully mixed or non-uniform. Non-uniform methods can be further divided into piston, stratified and task zone ventilation. In this paper, the theory, performance, practical applications, limitations and solutions pertaining to ventilation and air distribution methods are critically reviewed. Since many ventilation methods are buoyancy driving that confines their use for heating mode, some methods suitable for heating are discussed. Furthermore, measuring and evaluating methods for ventilation and air distribution are also discussed to give a comprehensive framework of the review

Green Design Studio: A modular-based approach for high-performance building design

Building energy and indoor air quality (IAQ) are of great importance to climate change and people’s health and wellbeing. They also play a key role in mitigating the risk of transmissions of infectious diseases such as COVID-19. Building design with high performance in energy efficiency and IAQ improvement can save energy, reduce carbon emissions, and improve human health. High-performance building (HPB) design at the early design stage is critical to building’s real performance during operation. Fast and reliable prediction of building performance is, therefore, required for HPB design during the early design iterations. A modular-based method to analyze building performance on energy efficiency, thermal comfort, IAQ, health impacts, and infection risks was developed, implemented, and demonstrated in this study. The modular approach groups the building technologies and systems to modules that can be analyzed at multi-scale building environments, from urban scale, to building, room, and personal scale. The proposed approach was implemented as a plugin on Rhino Grasshopper, a 3D architectural geometry modeling tool. The design and simulation platform was named Green Design Studio. Reduced-order physics-based models were used to simulate thermal, air, and mass transfer and storage in the buildings. Three cases were used as the study case to demonstrate the module-based approach and develop the simulation platform. Optimization algorithms were applied to optimize the design and settings of the building modules beyond the reference case. The case study shows that the optimal design of the small office determined by the developed platform can save up to 27.8% energy use while mitigating more than 99% infection risk compared to the reference case. It reveals that the optimization of green building design using the proposed approach has high potential of energy saving and IAQ improvement. In support of the application of the Green Design Studio platform, a database of green building technology modules for energy efficiency and IAQ improvement was created. Two selected emerging IAQ strategies were studied using the proposed approach and the developed tool, including the in-duct needlepoint bipolar ionizer and the combination of displacement ventilation and partitions. The in-duct ionization system can provide an equivalent single pass removal efficiency (SPRE) of 3.8-13.6% on particle removal without significant ozone and volatile organic compounds (VOCs) removal and generation with minimal energy use. The combined application of displacement ventilation and desk partitions can also effectively mitigate potential virus transmission through coughing or talking. The abundant performance data from experiments and detailed simulations for the studied technologies will be used by the database of the green building technologies and systems. It will allow these two technologies to be applied through the Green Design Studio approach during the early-design stage for a high-performance building. This can potentially help to address IAQ issues, particularly the airborne transmission of respiratory diseases, while maintaining high energy efficiency

Full Proceedings, 2018

Full conference proceedings for the 2018 International Building Physics Association Conference hosted at Syracuse University

Thermal Comfort under Transient Metabolic and Dynamic Localized Airflow Conditions Combined with Neutral and Warm Ambient Temperatures

Human thermal environments constitute complex combinations of various interacting thermal factors. The transient and non-uniform nature of those thermal factors further increases the complexity of the thermal comfort problem. The conventional approach to the thermal comfort problem has been simplifying the problem and providing steady thermal environments which would satisfy the majority of the people in a given space. However, several problems emerged with this approach. People became finely tuned to the narrow range of conditions and developed expectations for the same conditions which made them uncomfortable when there were slight deviations from those conditions. Also, the steady approach didn't solve the comfort problem because, in practice, people move between spaces, and thermal conditions such as metabolic rate, surface temperatures, airflow speed and direction vary in a typical day. A human subject test was designed to determine the transient relationship between the people and their environments. In the first part, thermal perceptions of people were taken during various metabolic rate conditions. In the second and the third parts, transient conditions of different thermal factors were created. Various combinations of airflow frequencies, airflow location around the body, metabolic rate, and room temperatures were tested for their individual and interaction effects of providing thermal comfort. The concept of Localized Dynamic Airflow was proposed in which room airflow was simply redirected to different parts of the body with a varying airflow speed. Results showed that males and females respond differently to the thermal conditions. The room temperatures they found neutral were significantly different. People‟s thermal comfort during transient metabolic conditions was similar to high metabolic conditions. This heightened response extended into the next ten minutes after the high metabolic conditions ended. Test results suggested that people tolerate higher temperatures during transient environmental conditions. The average response was for comfortable even during the high temperature (83°F) and high metabolic rate (4 met) conditions. Low energy use of the localized dynamic airflow and the increased room temperatures has significant potential for monetary savings

Cost effective and Non-intrusive occupancy detection in residential building through machine learning algorithm

Residential and commercial buildings consume more than 40% of energy and 76% of electricity in the U.S. Buildings also emit more than one-third of U.S. greenhouse gas emissions, which is the largest sector. A significant portion of the energy is wasted by unnecessary operations on heating, ventilation, and air conditioning (HVAC) systems, such as overheating/overcooling or operation without occupants. Wasteful behaviors consume twice the amount of energy compared to energy-conscious behaviors. Many commercial buildings utilize a building management system (BMS) and occupancy sensors to better control and monitor the HVAC and lighting system based on occupancy information. However, the complicated installation process of occupancy sensors and their long payback period have prevented consumers from adopting this technology in the residential sector. Hence, I explored a method to detect the presence of an occupant and utilize it to reduce energy wasting in residential buildings. Existing methods of occupancy detection often focus on directly measure occupancy information from environmental sensors. The validity of such a sensor network highly depends on the room configurations, so the approach is not readily transferrable to other residential buildings. Instead of direct measurement, the proposed scheme detects the change of occupancy in a building. The new scheme implements machine learning methods based on a sequence of human activities that happens in a short period. Since human activities are similar regardless of house floorplan, such an approach may lead to readily transferrable to other residential buildings. I explored three types of human activity sensor to detect door handle touch, water usage, and motion near the entrance, which are highly correlated with the change of occupancy. The occupancy change is not only based on one single human activity, it also depends on a series of human activities that happen in a short period, called event. As the events have different durations and cannot be readily applicable to existing machine learning models due to varying input matrix sizes. Hence, I devised a fixed format to summarize the event regardless of the total duration of the event. Then I used a machine learning model to identify the occupancy change based on the event data. The saving potential of occupancy driven thermostat is about 20 % of energy in residential buildings. However, the actual saving impact in any given house can vary significantly from the average value due to the large variety of residential buildings. Existing building simulation tools did not readily consider the random nature of occupancy and users’ comfort. For this reason, I explored a co-simulation platform that integrates an occupancy simulator, a cooling/heating setpoint control algorithm, a comfort level evaluator, and a building simulator together. I explored the annual energy saving impact of an occupancy-driven thermostat compare with a conventional thermostat. The simulation had been repeated in five U.S. cities (Fairbanks, New York City, San Francisco, Miami, and Phoenix) with distinctive climate zones

LICHT 2016 : Karlsruhe, 25. - 28. September ; Tagungsband - Proceedings ; [22. Gemeinschaftstagung = 22nd Associations’ Meeting]

Licht ist Forschungsgegenstand vieler Disziplinen: ob als Faktor in der Energieforschung, intelligente Smart-Home-Komponente in der IT-Technik, Werkzeug in Optik und Photonik oder Designelement in der Architektur. Mit diesen verschiedenen Aspekten befasst sich die Tagung „LICHT 2016“, die vom 25. bis 28. September in Karlsruhe stattfindet. Der Tagungsband enthält die Beiträge der 22. Gemeinschaftstagung der Licht-Gesellschaften Deutschlands, Österreichs, der Niederlande und der Schweiz