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| 1 | Advanced data analytics for enhancing building performances: From data-driven to big data-driven approaches显示文摘Buildings have a significant impact on global sustainability.During the past decades,a wide variety of studies have been conducted throughout the building lifecycle for improving the building performance.Data-driven approach has been widely adopted owing to less detailed building information required and high computational efficiency for online applications.Recent advances in information technologies and data science have enabled convenient access,storage,and analysis of massive on-site measurements,bringing about a new big-data-driven research paradigm.This paper presents a critical review of data-driven methods,particularly those methods based on larger datasets,for building energy modeling and their practical applications for improving building performances.This paper is organized based on the four essential phases of big-data-driven modeling,i.e.,data preprocessing,model development,knowledge post-processing,and practical applications throughout the building lifecycle.Typical data analysis and application methods have been summarized and compared at each stage,based upon which in-depth discussions and future research directions have been presented.This review demonstrates that the insights obtained from big building data can be extremely helpful for enriching the existing knowledge repository regarding building energy modeling.Furthermore,considering the ever-increasing development of smart buildings and IoT-driven smart cities,the big data-driven research paradigm will become an essential supplement to existing scientific research methods in the building sector. | Cheng Fan Da Yan Fu Xiao Ao Li Jingjing An Xuyuan Kang | 2021 | Building Simulation2021，14，1： | 10 |
| 2 | DeST 3.0:A new-generation building performance simulation platform显示文摘Buildings contribute to almost 30%of total energy consumption worldwide.Developing building energy modeling programs is of great significance for lifecycle building performance assessment and optimization.Advances in novel building technologies,the requirements of high-performance computation,and the demands for multi-objective models have brought new challenges for building energy modeling software and platforms.To meet the increasing simulation demands,DeST 3.0,a new-generation building performance simulation platform,was developed and released.The structure of DeST 3.0 incorporates four simulation engines,including building analysis and simulation(BAS)engine,HVAC system engine,combined plant simulation(CPS)engine,and energy system(ES)engine,connected by air loop and water loop balancing iterations.DeST 3.0 offers numerous new simulation features,such as advanced simulation modules for building envelopes,occupant behavior and energy systems,cross-platform and compatible simulation kernel,FMI/FMU-based co-simulation functionalities,and high-performance parallel simulation architecture.DeST 3.0 has been thoroughly evaluated and validated using code verification,inter-program comparison,and case-study calibration.DeST 3.0 has been applied in various aspects throughout the building lifecycle,supporting building design,operation,retrofit analysis,code appliance,technology adaptability evaluation as well as research and education.The new generation building simulation platform DeST 3.0 provides an efficient tool and comprehensive simulation platform for lifecycle building performance analysis and optimization. | Da Yan Xin Zhou Jingjing An Xuyuan Kang Fan Bu Youming Chen Yiqun Pan Yan Gao Qunli Zhang Hui Zhou Kuining Qiu Jing Liu Yan Liu Honglian Li Lei Zhang Hong Dong Lixin Sun Song Pan Xiang Zhou Zhe Tian Wenjie Zhang Ruhong Wu Hongsan Sun Yu Huang Xiaohong Su Yongwei Zhang Rui Shen Diankun Chen Guangyuan Wei Yixing Chen Jinqing Peng | 2022 | Building Simulation2022，15，11： | 5 |
| 3 | First experimental constraints on WIMP couplings in the effective field theory framework from CDEX显示文摘We present weakly interacting massive particles(WIMPs) search results performed using two approaches of effective field theory from the China Dark Matter Experiment(CDEX), based on the data from both CDEX-1B and CDEX-10 stages. In the nonrelativistic effective field theory approach, both time-integrated and annual modulation analyses were used to set new limits for the coupling of WIMP-nucleon effective operators at 90% confidence level(C.L.) and improve over the current bounds in the low mχregion. In the chiral effective field theory approach, data from CDEX-10 were used to set an upper limit on WIMP-pion coupling at 90% C.L. We for the first time extended the limit to the m_(χ)<6 GeV/c^(2) region. | Yi Wang Zhi Zeng Qian Yue LiTao Yang KeJun Kang YuanJing Li Mehment Agartioglu HaiPeng An JianPing Chang JingHan Chen YunHua Chen JianPing Cheng Cheng Yi Chiang WenHan Dai Zhi Deng ChangHao Fang XinPing Geng Hui Gong QiuJu Guo XuYuan Guo HongJian He Li He ShengMing He JinWei Hu TuChen Huang HanXiong Huang HaiTao Jia LiPing Jia Xi Jiang HauBin Li JianMin Li Jin Li MingXuan Li RenMingJie Li Xia Li YuLan Li Bin Liao FongKay Lin ShinTed Lin ShuKui Liu YanDong Liu Yu Liu YuanYuan Liu ZhongZhi Liu Hao Ma YuCai Mao QiYuan Nie JinHua Ning Hui Pan NingChun Qi Jie Ren XiChao Ruan ChangSong Shang Vivek Sharma Ze She Lakhwinder Singh Monoj Kumar Singh TianXi Sun ChangJian Tang WeiYou Tang Yang Tian GuangFu Wang Li Wang Qing Wang Yu Chen Wang YunXiang Wang Zhen Wang Henry Tsz-King Wong ShiYong Wu YuCheng Wu HaoYang Xing Yin Xu Tao Xue YuLu Yan Nan Yi ChunXu Yu HaiJun Yu JianFeng Yue Ming Zeng BingTao Zhang Lei Zhang FengShou Zhang ZhenYu Zhang KangKang Zhao MingGang Zhao JiFang Zhou ZuYing Zhou JingJun Zhu | 2021 | Science China(Physics,Mechanics & Astronomy)2021，64，8： | 3 |
| 4 | Clustering-based probability distribution model for monthly residential building electricity consumption analysis显示文摘Electricity is now the major form of energy used in residential buildings and has seen a significant increase in usage over the past decades.One of the main features of electricity use in residential buildings is the diversity of total electricity consumption and use patterns among households.Current models may not be able to simulate and generate electricity use curves or reflect the variations accurately.To fill this gap,this research simulates electricity use curves in residential buildings with a clustering-based probability distribution model.The model extracts feature parameters to represent the electricity use level and patterns and then conducts a two-step cluster analysis to identify the distinctions of both electricity use levels and patterns.Based on the clustering results,probability distributions are fitted for all feature parameters within each sub-cluster.The model is then validated with three validation approaches.Monthly electricity consumption in households of the Jiangsu Province,China,was studied to test the performance of the model.Lastly,this paper discusses the application of this model under different spatial resolutions and analyzes the temporal-relevant model features. | Jieyan Xu Xuyuan Kang Zheng Chen Da Yan Siyue Guo Yuan Jin Tianyi Hao Rongda Jia | 2021 | Building Simulation2021，14，1： | 1 |
| 5 | Similar physical entity matching strategy for mobile edge search显示文摘In recent years,a large number of intelligent sensing devices have been deployed in the physical world,which brings great difficulties to the existing entity search.With the increase of the number of intelligent sensing devices,the accuracy of the search system in querying the entities to match the user’s request is reduced,and the delay of entity search is increased.We use the mobile edge technology to alleviate this problem by processing user requests on the edge side and propose a similar physical entity matching strategy for the mobile edge search.First,the raw data collected by the sensor is lightly weighted and expressed to reduce the storage overhead of the observed data.Furthermore,a physical entity matching degree estimation method is proposed,in which the similarity between the sensor and the given sensor in the network is estimated,and the matching search of the user request is performed according to the similarity.Simulation results show that the proposed method can effectively reduce the data storage overhead and improve the precision of the sensor search system. | Puning Zhang Xuyuan Kang | 2020 | Digital Communications and Networks2020，6，2： | 0 |
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