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Quantification of how mechanical ventilation influences the airborne infection risk of CoVID-19 and HVAC energy consumption in office buildings

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Building Simulation 2023年第5期16卷 713-732页

作者： Zhihong Pang Xing Lu Zheng O’Neill mike walker’66 department of mechanical engineering texas a&m universitycollege stationtx 77843usa

This paper presents an EnergyPlus-based parametric analysis to investigate the infection risk of Coronavirus Disease 2019(CoVID-19)under different mechanical ventilation scenarios for a typical medium-sized office building in various climate zones.A Wells-Riley(WR)based Gammaitoni-Nucci(GN)model was employed to quantitatively calculate the airborne infection risk.The selected parameters for the parametric analysis include the climate zone,outdoor air fraction,fraction of infectors,quanta generation rate,and exposure time.The loss and deposition of particles are not considered.The results suggest that the CoVID-19 infection risk varies significantly with climate and season under different outdoor air fraction scenarios since the building heating and cooling load fundamentally impacts the supply airflow rate and thus directly influences the amount of mechanical ventilation,which determines the dilution ratio of contaminants.This risk assessment identified the climate zones that benefit the most and the least from increasing the outdoor air fraction.The climate zones such as 1A(Honolulu,HI),2B(Tucson,AZ),3A(Atlanta,GA),and 7(International Falls,MN)are the most energy-efficient locations when it comes to increasing the outdoor air fraction to reduce the CoVID-19 infection risk.In contrast,the climate zones such as 6A(Rochester,MN)and 6B(Great Falls,MT)are the least energy-efficient ones.This paper facilitates understanding a widely recommended CoVID-19 risk mitigation strategy(i.e.,increase the outdoor airflow rate)from the perspective of energy consumption.

关键词： CoVID-19 smart ventilation built environment infection risks building simulation office building

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From occupants to occupants:A review of the occupant information understanding for building HVAC occupant-centric control

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Building Simulation 2022年第6期15卷 913-932页

作者： Tao Yang Arkasama Bandyopadhyay Zheng O’Neill Jin Wen Bing Dong mike walker’66 department of mechanical engineering texas a&m universitycollege stationtx77843usa department of civil architectural&environmental engineeringdrexel universityphiladelphiapa19104usa department of mechanical and aerospace engineering syracuse universitysyracuseny13244usa

occupants are the core of the built environment.Traditional heating,ventilation,and air-conditioning(HVAC)systems operate with predefined schedules and maximum occupancy assumptions with no consideration of specific occupant information.These generalized assumptions usually do not align with the actual demand and result in over-conditioning and occupant discomfort.In recent years,with the aid of Information&Communication Technology(ICT)and Computer Science(CS),it is possible to acquire real-time and accurate occupant information to satisfy the exact thermal requirement through specific HVAC control in one particular built environment.This mechanism is called HVAC“occupant-centric Control(oCC).”HVAC oCC strategy starts with collecting the occupant’s information(e.g.,presence/absence)and then applies it to meet the occupant’s requirement(e.g.,thermal comfort).However,even though some research studies and field pilot demonstrations have been devoted to the field of oCC,there is a lack of systematic knowledge about occupant data,which is the principal component of oCC for HVAC researchers and practitioners.To fill this gap,this review paper discusses oCC with a particular emphasis on occupant information and investigates how this information can assist HVAC operation in providing an acceptable built environment in required spaces during the required time.We provide a fine-grained,comprehensive picture of occupant information,discuss its features,the modalities of information feed-in into the HVAC control,and the application of commonly utilized occupant information for oCC.

关键词： occupant information occupant-centric control smart building HVAC energy efficiency

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Extracting typical occupancy schedules from social media (ToSSM) and its integration with building energy modeling

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Building Simulation 2021年第1期14卷 25-41页

作者： Xing Lu Fan Feng Zhihong Pang Tao Yang Zheng O’Neill Department of Mechanical Engineering Texas A&M UniversityCollege StationTX77843USA

Building occupancy,one of the most important consequences of occupant behaviors,is a driving influencer for building energy consumption and has been receiving increasing attention in the building energy modeling community.With the vast development of information technologies in the era of the internet-of-things,occupant sensing and data acquisition are not limited to a single node or traditional approaches.The prevalence of social networks provides a myriad of publically available social media data that might contain occupancy information in the space for a given time.In this paper,we explore two approaches to extract the typical occupancy schedules for the input to the building energy simulation based on the data from social networks.The first approach uses text classification algorithms to identify whether people are present in the space where they are posting on social media.on top of that,the typical building occupancy schedules are extracted with assumed people counting rules.The second approach utilizes the processed Global Positioning System(GPS)tracking data provided by social networking service companies such as Facebook and Google Maps.Web scraping techniques are used to obtain and post-process the raw data to extract the typical building occupancy schedules.The results show that the extracted building occupancy schedules from different data sources(Twitter,Facebook,and Google Maps)share a similar trend but are slightly distinct from each other and hence may require further validation and corrections.To further demonstrate the application of the extracted Typical occupancy Schedules from Social Media(ToSSM),data-driven models for predicting hourly energy usage prediction of a university museum are developed with the integration of ToSSM.The results indicate that the incorporation of ToSSM could improve the hourly energy usage prediction accuracy to a small extent regarding the four adopted evaluation metrics for this museum building.

关键词： occupancy schedule social media building energy modeling data-driven models

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SPC and Kalman filter-based fault detection and diagnosis for an air-cooled chiller

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Frontiers of Electrical and Electronic Engineering in China 2011年第3期6卷 412-423页

作者： Biao SUN Peter B.LUH Zheng O’Neill Center for Intelligent and Networked Systems Department of AutomationTsinghua UniversityBeijing 100084China The Tsinghua-UTC Research Institute for Integrated Building Energy Safety and Control SystemTsinghua UniversityBeijing 100084China Department of Electrical and Computer Engineering University of ConnecticutStorrsCT 06269USA United Technology Research Center United Technologies CorporationHartfordCT 06108USA

Buildings worldwide account for nearly 40%of global energy consumption.The biggest energy consumer in buildings is the heating,ventilation and air conditioning(HVAC)systems.In HVAC systems,chillers account for a major portion of the energy consumption.Maintaining chillers in good conditions through early fault detection and diagnosis is thus a critical issue.In this paper,the fault detection and diagnosis for an air-cooled chiller with air coming from outside in variable flow rates is studied.The problem is difficult since the air-cooled chiller is operating under major uncertainties including the cooling load,and the air temperature and flow rate.A potential method to overcome the difficulty caused by the uncertainties is to perform fault detection and diagnosis based on a gray-box model with parameters regarded as constants.The method is developed and verified by us in another paper for a water-cooled chiller with the uncertainty of cooling load.The verification used a Kalman filter to predict parameters of a gray-box model and statistical process control(SPC)for measuring and analyzing their variations for fault detection and diagnosis.The gray-box model in the method,however,requires that the air temperature and flow rate be nearly constant.By introducing two new parameters and deleting data points with low air flow rate,the requirement can be satisfied and the method can then be applicable for an air-cooled chiller.The simulation results show that the method with the revised model and some data points dropped improved the fault detection and diagnosis(FDD)performance greatly.It can detect both sudden and gradual air-cooled chiller capacity degradation and sensor faults as well as their recoveries.

关键词： air-cooled chiller fault detection and diagnosis(FDD) statistical process control(SPC) Kalman filter

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Weights-Based Gravity Energy Storage Looks to Scale Up

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Engineering 2022年第7期8卷 3-6页

作者： Sean o’neill Senior Technology Writer

Innovative technology for gravity energy storage(GES),based on hoisting and lowering heavy weights to store and release energy in a highly sustainable manner,has now stepped onto the global stage.on 14 February 2022,Energy Vault Holdings,Inc.,began trading on the New York Stock Exchange,after merging with a special purpose acquisition company,Novus Capital Corporation II;the transaction raised 235 million USD[1].

关键词： trading raised store

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Solar Geoengineering to Reduce Global Warming—The outlook Remains Cloudy

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Engineering 2022年第2期8卷 6-9页

作者： Sean o’neill Senior Technology Writer

In March 2021,Australia’s Great Barrier Reef played host to a rare field test of marine cloud brightening(MCB)technology.Blasting a seawater mist into the air from the aft of a research ves-sel using a turbine outfitted with novel spray nozzles,researchers watched the resulting white plume rise into the sky(Fig.1)[1].over the last five years,the Reef has suffered multiple mass bleaching events because of ocean warming caused by climate change[2].The MCB project,led by senior lecturer Daniel Harrison of Southern Cross University,Coffs Harbour,Australia,is part of the Reef Restoration and Adaptation Program[3],a government-backed research and development initiative that aims to“develop,test and risk-assess novel interventions to help keep the Reef resilient.”

关键词： Solar warming ocean

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Climate Change Action Alights on Satellite Detection of Methane

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Engineering 2022年第9期16卷 9-12页

作者： Sean o’neill Senior Technology Writer

In an era of unwelcome broken records in climate change,2021delivered yet another.According to figures released in January2022 by the US National oceanic and Atmospheric Administration(NoAA)[1,2],the record for the annual net increase in atmospheric methane was broken for the second year in a row,hitting an estimated 17 parts per billion(ppb).The increase puts methane’s atmospheric concentration at 1909 ppb(Fig.1),more than 2.5times its pre-industrial levels[3].

关键词： atmospheric methane Action

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Machine Learning Turbocharges Structural Biology

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Engineering 2022年第5期8卷 9-11页

作者： Sean o’neill 机构不祥

on 28 January 2022,DeepMind Technologies announced the addition of the proteomes of 27 organisms to its AlphaFold Protein Structures Database(AlphaFold DB),a free online resource for sci-entists[1].DeepMind,the London-based,artificial intelligence(AI)-focused subsidiary of Google’s parent company,Alphabet,selected these proteomes in alignment with the priorities of the World Health organization.

关键词： Alpha subsidiary charges

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Two New Mega Dams Begin operating as Hydropower Industry Booms

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Engineering 2022年第11期18卷 9-11页

作者： Sean o’neill Senior Technology Writer

February 2022 saw the first official electricity produced by what will be,once fully operational,Africa’s largest hydropower dam,the Grand Ethiopian Renaissance Dam(GERD)(Fig.1)[1].It is just one of the latest milestones in an ongoing global boom in a hydropower dam industry pulled from the doldrums by the urgent need to produce climate-friendly energy for a global population with a growing demand for electricity[2].

关键词： Renaissance Grand Hydropower

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Direct Air Carbon Capture Takes Baby Steps——Giant Strides Are Needed

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Engineering 2022年第1期8卷 3-5页

作者： Sean o’neill Senior Technology Writer

In September 2021, the world’s largest industrial plant to pull carbon dioxide（Co;） directly out of the atmosphere officially became operational in Iceland. Designed and built by the Zurich,Switzerland-based company Climeworks, its "orca" facility-the company claims-can remove and permanently store 4000 t of Co;per year（Fig. 1） [1].

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