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Building Drag Parameterization Including Anisotropy and Its Coupling with the Weather Research and Forecasting Model 认领 引用
1
作者 Yuhang TIAN Zhenghui XIE +7 位作者 Jinbo XIE Binghao JIA Shuai SUN Peihua QIN Ruichao LI Longhuan WANG Heng YAN Yanbin YOU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第7期1461-1477,共17页
Buildings increase the urban surface roughness and reduce near-surface wind speeds due to the drag effect,which depends on the flow direction.In this study,a building drag parameterization scheme including the buildin... Buildings increase the urban surface roughness and reduce near-surface wind speeds due to the drag effect,which depends on the flow direction.In this study,a building drag parameterization scheme including the building anisotropy for all flow directions was developed through approximating buildings with elliptical columns to represent anisotropic frontal area index.The new scheme was coupled with the Weather Research and Forecasting(WRF)model to improve urban simulations in those including near-surface wind speeds.The conducted offline sensitivity tests with the developed scheme,using horizontal wind along different directions,show continuous transitions of drag coefficient and other variables depending on flow direction.The maximum difference of drag coefficient between the new and the original scheme reached 10%–20%of that from the original one.These monthly simulations of the WRF model with the new building drag scheme for Chengdu were conducted to validate the updated model against station observation and reanalysis data.Compared to the original scheme,the updated scheme reduces overestimation of 10-m wind speed by 0.1–0.2 m s−1(5%–15%of the original bias),overestimation of 2-m temperature by 0.1℃–0.4℃(20%–60%),and underestimation of 2-m relative humidity by 1%–3%(20%–60%).This is achieved by increasing the drag coefficient through an enhanced frontal area index and reducing wind speed.The diminished wind speed reduces sensible heat flux,enhances latent heat flux,and suppresses vertical motions,resulting in humidity accumulation and cooling in the lower atmosphere.These suggest that reasonable representation of the building anisotropy is important in researching urban climate. 展开更多
关键词 building drag parameterization frontal area index building anisotropy urban canopy model Weather Research and Forecasting model
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Resilient-based seismic design of a seismically isolated multitower-connected building 认领 引用
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作者 Wang Xinyu Xie Linlin +2 位作者 Zeng Demin Wang Tao Li Aiqun 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2026年第2期579-589,共11页
A three-tower connected reinforced concrete(RC)frame building was selected as a prototype building and used to investigate resilience-based seismic design,aiming to provide a reference for multitower-connected buildin... A three-tower connected reinforced concrete(RC)frame building was selected as a prototype building and used to investigate resilience-based seismic design,aiming to provide a reference for multitower-connected buildings by using seismic isolation.First,a seismic resilience assessment strategy was recommended based on the characteristics of the case study.Specifically,the restoration cost index was recommended as the ratio of the total repair cost of multiple towers and connection parts with respect to the current replacement cost.In contrast,repair time and casualties were recommended as the longest repair time and the highest casualties of multiple towers due to their uncoupled functions.The influences of the critical design parameter of the isolation system(i.e.,yield ratio)on the resilient performance of the entire building was investigated.Both the repair cost and time of the building decreased at decreasing yield ratios,which were attributed to the notable control of the maximum absolute floor acceleration.Only the case study,which showed a yield ratio of 2%,achieved the highest resilience level,as regulated by the relevant Chinese code.Hence,a 2%yield ratio is recommended for the conceptual design of seismically isolated multitower-connected buildings to achieve good seismic resilience. 展开更多
关键词 multitower-connected building seismic isolation yield ratio seismic responses resilience-based seismic design
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Incorporating delay propagation into decision-making for optimizing prefabricated building supply chain networks under uncertainty 认领 引用
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作者 Qiang DU Qian CHEN +3 位作者 Jing YANG Jiajie ZHOU Libiao BAI Xixi LUO 《ENGINEERING Management》 CSCD 2026年第2期363-385,共23页
Prefabricated buildings are crucial for the transformation of the construction industry,while the Prefabricated Building Supply Chain Network(PBSCN)that supports their implementation is subject to uncertainties in pro... Prefabricated buildings are crucial for the transformation of the construction industry,while the Prefabricated Building Supply Chain Network(PBSCN)that supports their implementation is subject to uncertainties in production,transportation,and installation.These uncertainties lead to schedule delays and cost increases,which significantly hinder the widespread adoption of prefabricated buildings.To address these issues,this paper develops a three-tier optimization model that integrates component factories,logistics providers,and contractors to improve resource allocation and reduce total costs.This model explicitly accounts for uncertainty-induced delay propagation across stages and incorporates its impacts into the decision-making process through work stoppage cost at the construction site.A Scenario-Based Stochastic Programming(SBSP)approach is employed to determine optimal decisions,while Monte Carlo Simulation(MCS)is utilized to generate representative scenarios.Furthermore,the proposed model is extended to incorporate a carbon trading mechanism to examine the interaction between environmental regulation and supply chain decisions.The model's effectiveness is validated through a hypothetical case adapted from a real-world project,in which the optimal solutions involved concentrating approximately 6%of orders in the baseline case and 33.0%35.5%in the largescale experiment.Results show that proactively accounting for uncertainties not only reduced costs but also strengthened coordination among entities to improve resource utilization.This paper provides practical decision support for PBSCN stakeholders,helping them mitigate risks,optimize order allocation,and improve overall supply chain performance in an uncertain environment. 展开更多
关键词 prefabricated buildings supply chain network coordination uncertainty management scenariobased stochastic programming cost optimization
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Data-driven method for seismic response prediction of rocking rigid bodies in buildings using deep neural networks 认领 引用
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作者 Cheng Qingle Song Zhengxuan +1 位作者 Xie Linlin Tian Yuan 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2026年第3期809-825,共17页
Furniture and equipment modeled as rocking rigid bodies within buildings are vulnerable to overturning during earthquakes,and their responses are strongly influenced by floor-level seismic amplification.However,predic... Furniture and equipment modeled as rocking rigid bodies within buildings are vulnerable to overturning during earthquakes,and their responses are strongly influenced by floor-level seismic amplification.However,predicting their seismic behavior typically involves analyses of building structural responses and rocking-body dynamics,making conventional approaches computationally expensive.Existing methods also struggle to adequately capture the nonlinear interactions among seismic motion characteristics,structural amplification effects,and the geometric properties of rocking bodies.To address this issue,this study proposes a data-driven method for predicting the seismic response of in-building rocking rigid bodies using a deep neural network(DNN).Floor seismic responses were obtained from city-scale nonlinear time-history analyses and used to calculate corresponding rocking-body responses.A multidimensional database was then established,covering various ground-motion intensity measures,building heights,and rigid-body geometries.Based on this database,a DNN model was developed for rapid overturning prediction.Results show that the proposed model achieves high computational efficiency and an accuracy of 94.37%on the test set,outperforming conventional machine learning methods.Dimensionality reduction further decreases input features and training time while preserving strong predictive performance.The proposed approach provides an efficient and intelligent framework for seismic assessment and risk analysis of rocking components in buildings. 展开更多
关键词 rocking rigid body seismic response prediction deep learning building response
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Quantitative analyzing method for floor acceleration amplification factor based on instrumented buildings 认领 引用
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作者 Wang Tao Pan Rui +2 位作者 Xu Guoshan Meng Liyan Liu Jisheng 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2026年第2期501-516,共16页
Precise analysis of the floor acceleration amplification(FAA)factor is crucial for accurately predicting the acceleration on acceleration-sensitive nonstructural components and estimating the seismic safety of nonstru... Precise analysis of the floor acceleration amplification(FAA)factor is crucial for accurately predicting the acceleration on acceleration-sensitive nonstructural components and estimating the seismic safety of nonstructural components.However,the existing literature on FAA did not analyze various influencing factors quantitatively.For solving this problem,one novel quantitative analyzing method of FAA considering various influencing factors in terms of structural type,structural height,site category,structural period,relative height and ground motion intensity based on instrumented buildings data from the Center for Engineering Strong Motion Data(CESMD)is proposed.The analysis results revealed that the site categories can significantly affect the FAA values of various types of structures,however,which has not been emphasized in previous studies.Correlation analysis reveals that the relative height is strongly correlated with the FAA,which is consistent with several seismic design codes.While,the parameters in terms of the site category,structural height and structural type also significantly correlated with the FAA.The results indicate that these three factors should be incorporated into the seismic design code.This study offers valuable insights and recommendations for the design of acceleration-sensitive nonstructural components in terms of FAA. 展开更多
关键词 floor acceleration amplification factor instrumented buildings acceleration-sensitive nonstructural components seismic performance site categories correlation analysis
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Application of tuned viscous mass dampers for seismic response control of industrial buildings coupled with mechanical equipment 认领 引用
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作者 Zhu Zhengrong Zhou Yun +2 位作者 Tan Zhongkun He Hui Zhou Xiaofeng 《Earthquake Engineering and Engineering Vibration》 SCIE EI CSCD 2026年第1期187-201,共15页
Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the... Although the effectiveness of a tuned viscous mass damper(TVMD)as an inerter-based device for vibration control in civil structures has been thoroughly investigated,there is a lack of systematic research regarding the application of TVMDs for seismic response control of industrial buildings coupled with mechanical equipment.Therefore,this study proposes ungrounded and grounded TVMDs to effectively utilize the mass of the mechanical equipment and fully exploit the capabilities of the inerter element.An optimal design methodology is developed by pursuing the maximum effective damping ratio and seeking the most rational TVMD control scheme.Validation of TVMD control performance is conducted through time-history analysis based on 20 real seismic ground motions recommended by ATC-40,and by providing a barrel mixer industrial building as a real-life numerical example.The results show that both an ungrounded and grounded TVMD can effectively mitigate the seismic response of the primary structure.Compared to the traditional tuned mass damper(TMD),TVMDs can obtain improved control performance for a given equipment mass ratio.Moreover,an ungrounded TVMD and a TMD show similar working mechanisms that tend to release the displacement of equipment to keep their optimal state,whereas equipment displacement for a grounded TVMD should be strictly limited to provide sufficient anti-force. 展开更多
关键词 tuned viscous mass damper inerter-based devices vibration control industrial building
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A MCG-GFAM-MRDCM Model for Accurate Building Electricity Load Forecasting 认领 引用
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作者 Chuan Lin Weixian Chen Guangtao Hao 《Energy Engineering》 EI 2026年第8期208-237,共30页
Accurate building electricity load forecasting(BELF)can provide a regulatory basis for building energy management systems and promote the transition of buildings toward low-carbon and intelligent operation modes.Howev... Accurate building electricity load forecasting(BELF)can provide a regulatory basis for building energy management systems and promote the transition of buildings toward low-carbon and intelligent operation modes.However,building electricity load is influenced by historical loads,as well as outside environmental conditions such as humidity and temperature,which reduces the prediction accuracy of models.To tackle these challenges,this study presents a BELF model,which consists of a modal component grouping approach,grouped feature attention mechanism,and multi-scale residual depthwise convolution memory module.First,the modal component grouping method analyzes building electricity load in the time domain,frequency domain(via fast fourier transform,FFT),and complexity(via sample entropy,SE),and then performs clustering to achieve precise decomposition of load components with different fluctuation characteristics.Second,the grouped feature attention mechanism assigns suitable importance to various input features to emphasize key factors affecting prediction accuracy.Third,the multi-scale residual depthwise convolution memory module mitigates the impact of long and short-term load variations on BELF by employing residual blocks of depthwise convolution layers with different kernel sizes.Meanwhile,gated recurrent units are used to identify the time-dependent trends of building load.Experimental results on public buildings show that the proposed model outperforms existing models,achieving more than 2.4%improvement in MAPE prediction performance. 展开更多
关键词 Building electricity load forecasting modal component grouping method depthwise convolutional neural network attention mechanism
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Feature-based molecular networking and building blocks identification advance novel natural products characterization:Sesquiterpene-chromone hybrids in agarwood as an application 认领 引用
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作者 Qian Wang Han Li +5 位作者 Huiting Liu Yujie Pei Pengfei Tu Huixia Huo Jun Li Yuelin Song 《Journal of Pharmaceutical Analysis》 SCIE CAS CSCD 2026年第3期886-888,共3页
As important sources of new drugs,natural products(NPs)are conceptually biosynthesized from simple structural pioneers(i.e.building blocks).The traditional non-targeted purification strategy extensively suffers from t... As important sources of new drugs,natural products(NPs)are conceptually biosynthesized from simple structural pioneers(i.e.building blocks).The traditional non-targeted purification strategy extensively suffers from the time-consuming and laborious bottlenecks.Fortunately,liquid chromatography–mass spectrometry/mass spectrometry(LC–MS/MS)-guided separations widely succeed in recent decades.However,it is still challenging for LC–MS/MS to precisely capture new NPs.Efficiently extracting information from the chaotic chemical composition and confident structural annotation are two primary technical barriers for pursuing the interesting structures,particularly those exhibiting trace distributions and high-level structural complexity.Here,to provide accurate guidance for the follow-up phytochemical purification,molecular defect filtering(MDF)and feature-based molecular networking(FBMN)[1]were incorporated to explore NPs and thereafter,bottom-up structural analysis was undertaken through identifying building blocks with full exciting energy ramp(FEER)-MS 3 matching.Sesquiterpene-chromone hybrids(SCHs)structurally configured by two building blocks such as units A(chromone)and B(sesquiterpene)[2]in agarwood were characterized as a proof-of-concept.Twenty-five SCHs were captured and identified.Thereof,seven new SCHs were purified with a LC–MS/MS-guided manner and annotated using nuclear magnetic resonance(NMR)spectroscopy to justify the proposed structures.Moreover,their cell-protective and anti-inflammatory activities were evaluated.Together,the incorporation of post-acquisition data processing strategies and FEER-MS 3 spectrum matchingassisted building blocks identification facilitated novel NPs exploration and purification. 展开更多
关键词 sesquiterpene chromone hybrids agarwood liquid chromatography mass spectrometry mass spectrometry extracting information feature based molecular networking molecular defect filtering nuclear magnetic resonance spectroscopy building blocks identification
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Impact of urban heat island and global warming on multi-energy complementarity optimization of buildings:application to typical office buildings in Hangzhou,China 认领 引用
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作者 Qingqing MIAO Xiaoyu LUO +5 位作者 Jiang LU Weijun GAO Yucong XUE Yifan FAN Jian GE Jiahong ZHAO 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2026年第6期640-658,I0065-I0073,共19页
Amid global warming and urbanization,building energy systems face the dual challenge of balancing growth in energy demand with environmental sustainability and resistance to future climate change.This study proposes a... Amid global warming and urbanization,building energy systems face the dual challenge of balancing growth in energy demand with environmental sustainability and resistance to future climate change.This study proposes a predictive framework that integrates the effects of future climate change and urban microclimate into energy consumption prediction and energy system optimization for typical office buildings in Hangzhou,China.First,optimal general circulation models(GCMs)from CMIP6 are selected through a performance evaluation,and statistical downscaling is employed to generate future typical meteorological year(TMY)data.Next,the urban weather generator(UWG)is used to simulate urban heat island(UHI)effects.Empirical formulas are applied to calculate urban wind speeds,while DesignBuilder is used to model solar radiation and hourly energy consumption.These data are then used to optimize the building energy system.The results reveal that future climate change significantly increases cooling demand(28.9%-103.0%)and reduces heating demand(19.7%-52.6%),with urban microclimates further amplifying these trends.The energy system optimization demonstrates that the net present value(NPV)of future climate and urban microclimate scenarios is 5.1%-16.7%higher than that of historical climate scenarios.Additionally,future climate scenarios result in higher peak energy demand and thus necessitate larger system capacities to ensure reliability.While the initial required investment is higher,buildings optimized to account for global warming are more reliable and carry lower operational costs.We comprehensively quantify the effect of future urban microclimate on building energy systems,emphasizing its critical role in energy system planning and providing insights for addressing the challenges of climate change and urbanization. 展开更多
关键词 Future climate change Urban microclimate Building energy performance Building energy system Multi-objective optimization
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How interactions between buildings and green spaces influence urban thermal environments across local climate zones 认领 引用
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作者 Donghui Bai Chunping Miao +2 位作者 Wei Cao Zhe Zhang Yu Guan 《Ecological Frontiers》 CSCD 2026年第1期401-411,共11页
Local Climate Zones(LCZs)provide a standardized framework for analyzing urban thermal environment.Examining the interactive effects of building and green space patterns on land surface temperature(LST)within LCZs is e... Local Climate Zones(LCZs)provide a standardized framework for analyzing urban thermal environment.Examining the interactive effects of building and green space patterns on land surface temperature(LST)within LCZs is essential for uncovering urban cooling mechanisms and developing strategies for heat-mitigation urban design.Therefore,this study employed one-way ANOVA and Duncan's multiple comparison to test compare the significant differences of LST among LCZs 1-6,and applied the XGBoost model to quantify the interactive effects of building and green space indicators on LST,and to identify the threshold ranges of their cooling effects.The results showed that LCZ 2 exhibited the highest LST,while LCZ 4 recorded the lowest.Average building volume(BAV),building coverage ratio(BCR),green cover area(GCA),and the total edge length of green space(GTE)were identified as the key indicators driving the interactive effects on LST.In LCZ 2,when BAV exceeded 1800 m3,the interaction of higher GCA and GTE contributed to lower LST.When BCR was less than 0.6 in LCZs 4-5,lower GCA and GTE values enhanced the LST reduction.The results provided a strategic basis for urban thermal environment mitigation and sustainable development under the LCZ framework. 展开更多
关键词 Building morphology Green spaces LST LCZ Interaction effect
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Recent Advancements in Photocatalysts for Intelligent Building Materials 认领 引用
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作者 Fan Li Shuo Yang +2 位作者 Ting Sun Yongsheng Xu Wenchao Peng 《Transactions of Tianjin University》 EI CAS 2026年第1期64-78,共15页
Photocatalysis—a green and energy-efficient technology for environmental remediation and energy conversion—has recently demonstrated broad application potential in intelligent building materials.This review systemat... Photocatalysis—a green and energy-efficient technology for environmental remediation and energy conversion—has recently demonstrated broad application potential in intelligent building materials.This review systematically summarizes recent advancements in incorporating photocatalytic materials into building applications,focusing on two main scenarios:pavement and wall surfaces.In pavement systems,photocatalytic materials are primarily employed to degrade pollutants such as NOxand volatile organic compounds,thereby actively reducing emissions.In wall applications,the emphasis is on imparting intelligent maintenance functions,including self-cleaning,antibacterial activity,and air purification.We provide a comprehensive analysis of the performance of various photocatalytic materials,their incorporation methods,and their effects on mechanical properties and environmental durability.Building on this analysis,we propose design principles for photocatalytic building materials that balance catalytic efficiency with cost,enhance mechanical stability,and preserve the intrinsic functions of building components.Finally,we outline future research directions,emphasizing the significant potential of photocatalytic building materials in advancing green construction and sustainable development. 展开更多
关键词 Photocatalysis Intelligent building materials Pollutant removal Design principles
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Probabilistic assessment of high-rise buildings with fluid viscous dampers under hurricane wind loads 认领 引用
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作者 Iván F.HUERGO Josue X.ROCHA +2 位作者 Octavio F.URIBE Miguel Angel MENDOZA-LUGO Oswaldo MORALES-NÁPOLES 《ENGINEERING Structure and Civil Engineering》 SCIE EI CAS CSCD 2026年第3期580-604,共25页
Current wind design codes incorporate turbulence through gust factors and rely on historical wind data,including tropical cyclones.While generally conservative,standard code wind profiles and spectra do not fully repr... Current wind design codes incorporate turbulence through gust factors and rely on historical wind data,including tropical cyclones.While generally conservative,standard code wind profiles and spectra do not fully reproduce the vertical distribution and dynamic characteristics of hurricane winds,particularly in the supergradient region near the eyewall,and can sometimes underestimate tail risks,low-probability,high-impact events,as observed during Hurricane Otis in Acapulco(2023).This study probabilistically evaluates wind-induced vibrations in high-rise buildings with different lateral resisting systems equipped with fluid viscous dampers(FVDs),under non-tropical storm and tropical cyclone conditions.Along-wind loads were modeled in the time domain as stationary,multidimensional stochastic processes and analyzed using one million Monte Carlo simulations and Incremental Dynamic Analysis on the DelftBlue supercomputer.Statistical distributions of responses,bivariate dependence via copulas,and fragility curves were obtained.Results show that wind type,structural deformation mode,and damper properties significantly affect response distributions,correlation structures,and failure probabilities.FVDs effectively reduce structural dynamic response,improving serviceability,while increased shear stiffness further reduces fragility.Modeling hurricane winds as nontropical storms can overestimate damper effectiveness.These findings provide insights for refining wind codes and designing high-rise buildings that remain safe and functional under extreme events. 展开更多
关键词 bivariate analysis fluid viscous dampers fragility curves high-rise buildings hurricane wind loads Monte Carlo simulation
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Towards Resilient Cities:Robust Selection of Rooftop Renewable Energy Technologies in Mediterranean Multifamily Buildings 认领 引用
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作者 Federico Minelli Diana D’Agostino +1 位作者 Vennapusa Jagadeeswara Reddy Panagiotis Michailidis 《Energy Engineering》 EI 2026年第6期469-511,共43页
This study investigates the problem of prioritizing rooftop renewable energy(RE)system configurations for a multi-family residential building in Mediterranean climate.The analysis focuses on fixed-tilt photovoltaics(P... This study investigates the problem of prioritizing rooftop renewable energy(RE)system configurations for a multi-family residential building in Mediterranean climate.The analysis focuses on fixed-tilt photovoltaics(PV),single-axis and dual-axis tracking PV,and small vertical-axis wind turbines(VAWT),each assessed with and without lithium-ion storage.A co-simulation framework is used,coupling EnergyPlus building-HVAC system simulation with PV and wind generation modeling and rule-based battery dispatch to evaluate hourly demand–supply interactions.Three decision criteria are considered for each alternative:total system cost,annual building electric energy demand reduction,and net avoided life-cycle emissions.Stakeholder preferences are elicited via Analytic Hierarchy Process(AHP),considering the building owner as the decision-maker.The design alternatives are then ranked with three multicriteria decision-making(MCDM)methods(TOPSIS,ARAS,and COPRAS)and a global rank is computed through an ensemble(Borda)aggregation.Results show that due to roof-area constraints,dense fixed-tilt PV system layouts are favored to achieve maximum annual generation(≈60.8 MWh per year),whereas tracking systems achieve higher specific yield but lower system capacity per roof because of increased need of spacing and maintenance corridors.Design alternatives that incorporate energy storage significantly raise self-consumption and demand reduction.Indeed,fixed PV with large storage can reach high annual coverage of building electric energy consumption,while the same PV without storage can reduce it by~43.7%.VAWT options contribute modestly to energy demand reduction given unfavorable urban wind conditions and their shorter lifetime.Under owner-centric weights that emphasize cost,the ensemble ranking prioritizes low-CAPEX PV solutions(dual-axis PV without storage,single-axis PV without storage,single-axis PV with small storage,and fixed-tilt PV).Instead,design alternatives encompassing large energy storage and small-wind alternatives occupy the lower ranks.The findings provide useful insights and a stakeholder-wise tool to select rooftop RE technologies on Mediterranean residential buildings,balancing economic feasibility with energy and environmental performance. 展开更多
关键词 Building energy efficiency renewable energy systems dynamic energy simulation multi-criteria decision-making
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Adaptive regional segmentation and fitting-based building LOD reconstruction method 认领 引用
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作者 Bowen LI Xukun SHEN Yong HU 《虚拟现实与智能硬件（中英文）》 EI CSCD 2026年第2期202-218,共17页
Reconstructing accurate urban building models remains challenging because of large-scale variability and complex topologies.We introduce a practical multi-step framework that reconstructs a single building from a dens... Reconstructing accurate urban building models remains challenging because of large-scale variability and complex topologies.We introduce a practical multi-step framework that reconstructs a single building from a dense triangular mesh by explicitly exploiting its block-wise composition.The pipeline first partitioned the mesh into spatially coherent regions,then extracted height-aware contours,and classified the geometry into facades,roofs,and appurtenances.For each part,we performed contour-guided vectorized modeling with profile fitting and consistency constraints,producing watertight,semantically structured models at the level of detail(LOD)2.3.The interactive refinement module further supported user adjustments to resolve rare failures and enforced design regularity.The proposed decomposition and layered fitting yielded compact outputs while preserving the salient geometry and made the reconstruction robust across scales and moderate noise.We also analyzed the modeling assumptions and implementation details to ensure reproducibility.Overall,this study offers a component-aware,engineering-ready solution for converting unstructured meshes into structured building models that are amenable to downstream urban modeling and visualization. 展开更多
关键词 Building reconstruction Block-wise segmentation Contour-guided vectorization LOD Interactive refinement Watertight modeling
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Tri-Band Regulation and Split-Type Smart Photovoltaic Windows for Thermal Modulation of Energy-Saving Buildings in All-Season 认领 引用
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作者 Qian Wang Zongxu Na +7 位作者 Jianfei Gao Li Yu Yuanwei Chen Peng Gao Yong Ding Songyuan Dai Mohammad Khaja Nazeeruddin Huai Yang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第4期651-662,共12页
Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable devel... Energy-saving buildings(ESBs)are an emerging green technology that can significantly reduce building-associated cooling and heating energy consumption,catering to the desire for carbon neutrality and sustainable development of society.Smart photovoltaic windows(SPWs)offer a promising platform for designing ESBs because they present the capability to regulate and harness solar energy.With frequent outbreaks of extreme weather all over the world,the achievement of exceptional energy-saving effect under different weather conditions is an inevitable trend for the development of ESBs but is hardly achieved via existing SPWs.Here,we substantially reduce the driving voltage of polymerdispersed liquid crystals(PDLCs)by 28.1%via molecular engineering while maintaining their high solar transmittance(Tsol=83.8%,transparent state)and solar modulating ability(ΔTsol=80.5%).By the assembly of perovskite solar cell and a broadband thermal-managing unit encompassing the electrical-responsive PDLCs,transparent high-emissivity SiO2 passive radiation-cooling,and Ag low-emissivity layers possesses,we present a tri-band regulation and split-type SPW possessing superb energy-saving effect in all-season.The perovskite solar cell can produce the electric power to stimulate the electrical-responsive behavior of the PDLCs,endowing the SPWs zero-energy input solar energy regulating characteristic,and compensate the daily energy consumption needed for ESBs.Moreover,the scalable manufacturing technology holds a great potential for the real-world applications. 展开更多
关键词 Smart photovoltaic windows Polymer-dispersed liquid crystals Passive radiative cooling Tri-band regulation Energy-saving buildings
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Distributed context-aware Transformer-enabled dynamic energy consumption prediction for smart building networks 认领 引用
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作者 Rui Dai Ge Bai 《Digital Communications and Networks》 SCIE EI CSCD 2026年第4期640-648,共9页
The integration of communication networks and artificial intelligence enables the effective collection of data over smart building networks,facilitating more accurate predictions of Building Energy Consumption(BEC).Ho... The integration of communication networks and artificial intelligence enables the effective collection of data over smart building networks,facilitating more accurate predictions of Building Energy Consumption(BEC).However,existing schemes for BEC prediction suffer from limited dynamic adaptability,risks of privacy leakage,and the inability to accurately capture actual energy consumption patterns.To improve prediction accuracy while ensuring privacy and dynamic adaptability,we propose a novel BEC prediction design that incorporates dynamic threshold participation and privacy-preserving mechanisms.Specifically,we design a three-tier network architecture integrated with threshold participation tokens to support dynamic access and dropout of building entities during the BEC model construction process.Furthermore,we develop a Context-Aware Transformer(CAT)network integrated into Federated Learning(FL)to enhance feature sensitivity and facilitate the sharing of knowledge derived from Internet of Things(IoT)data and BEC features.Finally,we evaluate the performance of our design using real-world data,and the results demonstrate that our design achieves superior performance in distributed BEC prediction. 展开更多
关键词 Smart building Dynamic BEC prediction Context-aware Transformer Privacy preservation Federated learning
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Vision-Based Crack Detection for Wall-Climbing Robot on Building Surface 认领 引用
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作者 Xianghui Li Xin Fu +2 位作者 Libo Pan Fancong Zeng Zhijiang Zuo 《Structural Durability & Health Monitoring》 EI 2026年第2期418-439,共22页
The present study proposes an autonomous visual inspection system based on Wall-Climbing Robot(WCR),with a view to addressing the shortcomings of traditional building crack detection methods,namely their low measureme... The present study proposes an autonomous visual inspection system based on Wall-Climbing Robot(WCR),with a view to addressing the shortcomings of traditional building crack detection methods,namely their low measurement accuracy,high manual dependence and insufficient environmental adaptability.The system has been developed to construct a crack recognition model with robust illumination adaptation by fusing the improved YOLOv5s target detection algorithm with the Canny edge enhancement algorithm.The system has been realized as a lightweight deployment on an embedded device(MaixCAM).The robot platform employs a design scheme integrating a dual-chamber negative pressure adsorption mechanism and a differential drive system,which effectively addresses the key technical challenges of stable motion and real-time image acquisition on the vertical wall.Concurrently,the embedded vision processing module accomplishes efficient data parsing within dynamic environments.The experimental findings demonstrate that the system’s detection accuracy consistently maintains a range of 88.3%to 95.6%under conditions of 1000-50 lux illumination.In comparison with conventional detection methods,the recognition accuracy of various types of building cracks is enhanced by 17.3%.This study proposes a pioneering technical solution for the intelligent detection of complex building surface defects,which holds significant engineering application value. 展开更多
关键词 Crack detection wall-climbing robot autonomous visual inspection system building surface YOLOv5s Canny edge enhancement
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Numerical Simulation of Heat Transfer through Porous Hollow Building Block 认领 引用
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作者 Marina Astanina Igor Miroshnichenko +1 位作者 Gennadii Shashkin Mikhail Sheremet 《Frontiers in Heat and Mass Transfer》 EI CAS 2026年第2期269-287,共19页
This paper explores the thermal behavior of a composite building element consisting of two air cavities inside a porous layer under isothermal heating of the side walls.The system presents a model of a thermal protect... This paper explores the thermal behavior of a composite building element consisting of two air cavities inside a porous layer under isothermal heating of the side walls.The system presents a model of a thermal protection element or building envelope where heat transfer occurs through combined conduction in the porous medium and natural convection in the air gaps.The mathematical formulation is based on the Navier-Stokes equations and the Darcy-Brinkman formulation for the porous structure.The natural convection problem has been solved using theψ-ω-θformulation in dimensionless form(ψ—stream function,ω—vorticity,θ—temperature).The main heat transfer characteristics have been found to be strongly influenced by the governing parameters:Ra(the Rayleigh number),Da(Darcy number),ε(material porosity),and lx,ly(the size of the air gaps).Key findings:increasing the Rayleigh number from 104 to 106 enhances the mean Nusselt number from approximately 0.9 to 3.7 with intensification of convective heat transfer.Variations in the Darcy number over two orders of magnitude(10-4 to 10-2)result in a similar change in the mean Nusselt number.Increasing porosity fromε=0.1 toε=0.8 reduces the Nusselt number by less than 6%.The analysis of air cavity geometry shows that enlarging cavity dimensions increases flow intensity but produces only a moderate enhancement in heat transfer.Practical implications:optimal thermal insulation is achieved with highporosity foam concrete(ε≥0.6)combined with low permeability(Da≤10-4)and minimal air cavity dimensions.In this case,convective circulation is suppressed,and heat transfer remains conduction dominated with minimum values of the mean Nusselt number.The proposed model provides a physically consistent description of thermal transport in hybrid porous/fluid configurations and can serve as a basis for optimizing the thermal design of energy-efficient insulation structures and passive cooling devices. 展开更多
关键词 Hollow building block conjugate heat transfer thermal insulation free convection porous medium Brinkman-extended Darcy model air cavities
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Federated Deep Learning in Intelligent Urban Ecosystems:A Systematic Review of Advancements and Applications in Smart Cities,Homes,Buildings,and Healthcare Systems 认领 引用
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作者 Muhammad Adnan Tariq Sunawar Khan +5 位作者 Tehseen Mazhar Tariq Shahzad Sahar Arooj Khmaies Ouahada Muhammad Adnan Khan Habib Hamam 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第3期218-267,共50页
The contemporary smart cities,smart homes,smart buildings,and smart health care systems are the results of the explosive growth of Internet of Things(IoT)devices and deep learning.Yet the centralized training paradigm... The contemporary smart cities,smart homes,smart buildings,and smart health care systems are the results of the explosive growth of Internet of Things(IoT)devices and deep learning.Yet the centralized training paradigms have fundamental issues in data privacy,regulatory compliance,and ownership silo alongside the scaled limitations of the real-life application.The concept of Federated Deep Learning(FDL)is a privacy-by-design method that will enable the distributed training of machine learning models among distributed clients without sharing raw data and is suitable in heterogeneous urban settings.It is an overview of the privacy-preserving developments in FDL as of 2018-2025 with a narrow scope on its usage in smart cities(traffic prediction,environmental monitoring,energy grids),smart homes/buildings/IoT(non-intrusive load monitoring,HVAC optimization,anomaly detection)and the healthcare application(medical imaging,Electronic Health Records(EHR)analysis,remote monitoring).It gives coherent taxonomy,domain pipelines,comparative analyses of privacy mechanisms(differential privacy,secure aggregation,Homomorphic Encryption(HE),Trusted Execution Environments(TEEs),blockchain enhanced and hybrids),system structures,securityobustness defense,deployment/Machine Learning Operation(MLOps)issues,and the longstanding challenges(non-IID heterogeneity,communication efficiency,fairness,and sustainability).Some of the contributions made are structured comparisons of privacy threats,practical design advice on urban areas,recognition of open problems,and a research roadmap into the future up to 2035.The paper brings out the transformational worth of FDL in building credible,scalable,and sustainable intelligent urban ecosystems and the need to do further interdisciplinary research in standardization,real-world testbeds,and ethical governance. 展开更多
关键词 Federated deep learning(FDL) privacy-preserving AI smart cities smart homes/buildings federated healthcare intelligent urban ecosystems IoT
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Curtain Wall Systems as Climate-Adaptive Energy Infrastructures:A Critical Review of Their Role in Sustainable Building Performance 认领 引用
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作者 Samira Rastbod Mehdi Jahangiri +1 位作者 Behrang Moradi Haleh Nazari 《Energy Engineering》 EI 2026年第1期27-55,共29页
Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive exa... Curtain wall systems have evolved from aesthetic facade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness.This reviewpresents a comprehensive examination of curtain walls from an energy-engineering perspective,highlighting their structural typologies(Stick and Unitized),material configurations,and integration with smart technologies such as electrochromic glazing,parametric design algorithms,and Building Management Systems(BMS).Thestudy explores the thermal,acoustic,and solar performance of curtain walls across various climatic zones,supported by comparative analyses and iconic case studies including Apple Park,Burj Khalifa,and Milad Tower.Key challenges—including installation complexity,high maintenance costs,and climate sensitivity—are critically assessed alongside proposed solutions.A central innovation of this work lies in framing curtain walls not only as passive architectural elements but as dynamic interfaces that modulate energy flows,reduce HVAC loads,and enhance occupant comfort.The reviewed data indicate that optimized curtain wall configurations—especially those integrating electrochromic glazing and BIPV modules—can achieve annual energy consumption reductions ranging fromapproximately 5%to 27%,depending on climate,control strategy,and facade typology.The findings offer a valuable reference for architects,energy engineers,and decision-makers seeking to integrate high-performance facades into future-ready building designs. 展开更多
关键词 Curtain wall systems energy efficiency climate-responsive design smart facades electrochromic glass parametric architecture building envelope technologies
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