The Trombe wall is a passive indirect heating system which should be used in Cusco,Peru to improve thermal conditions against the typical frosts and low temperatures during winter in the high Andean regions.Due to thi...The Trombe wall is a passive indirect heating system which should be used in Cusco,Peru to improve thermal conditions against the typical frosts and low temperatures during winter in the high Andean regions.Due to this problem,the use of a modified Trombe wall with insertion of porous medium is proposed to improve thermal comfort in flat buildings in Cusco.This research aims to analyse and compare the performance of dwellings without Trombe wall,with traditional Trombe wall,and with Trombe wall with glass and plastic pellets insertion in thermal comfort improvement.Autodesk■CFD was used to simulate and analyse the system.The simulation was performed with three prototype flats(55 m^(2),75 m^(2) and 95 m^(2))for six months of the year.From the results obtained,the level of thermal comfort in the traditional scenarios is low with an average PMV of-1.86,in the scenarios with Trombe wall is good and in the scenarios with Trombe wall with insertion of porous medium is slightly better than the previous one,reaching an average PMV of+0.10 and a temperature of 21.90℃.The study carried out is important because it represents an efficient eco-sustainable heating alternative that improves the thermal comfort sensation in houses during the coldest months of the year.展开更多
Advanced data mining methods have shown a promising capacity in building energy management.However,in the past decade,such methods are rarely applied in practice,since they highly rely on users to customize solutions ...Advanced data mining methods have shown a promising capacity in building energy management.However,in the past decade,such methods are rarely applied in practice,since they highly rely on users to customize solutions according to the characteristics of target building energy systems.Hence,the major barrier is that the practical applications of such methods remain laborious.It is necessary to enable computers to have the human-like ability to solve data mining tasks.Generative pre-trained transformers(GPT)might be capable of addressing this issue,as some GPT models such as GPT-3.5 and GPT-4 have shown powerful abilities on interaction with humans,code generation,and inference with common sense and domain knowledge.This study explores the potential of the most advanced GPT model(GPT-4)in three data mining scenarios of building energy management,i.e.,energy load prediction,fault diagnosis,and anomaly detection.A performance evaluation framework is proposed to verify the capabilities of GPT-4 on generating energy load prediction codes,diagnosing device faults,and detecting abnormal system operation patterns.It is demonstrated that GPT-4 can automatically solve most of the data mining tasks in this domain,which overcomes the barrier of practical applications of data mining methods in this domain.In the exploration of GPT-4,its advantages and limitations are also discussed comprehensively for revealing future research directions in this domain.展开更多
Due to the majority of time people spent indoors,indoor air quality is not only critical to people’s health,comfort,but can also significantly influence occupants perception on indoor environment.Air quality is close...Due to the majority of time people spent indoors,indoor air quality is not only critical to people’s health,comfort,but can also significantly influence occupants perception on indoor environment.Air quality is closely related to many factors including thermal parameters,pollutant concentrations,and ventilation performance.However,the current building indoor air quality evaluation method is based the objective measurement of indoor parameters,without considering occupants’subjective perception.This paper is aimed at summarizing a profound review on the PAQ evaluation method.Comparisons among various PAQ evaluating methods with advantages,similarities and differences were conducted.Analysis of literatures about indoor air quality in Chinese residential buildings field is also summarized,and discussion on the subjective influence of temperature and relative humidity,venti-lation performance,volatile organic compounds(VOCs)concentration,and particulate matters on perceived air quality is carried out.展开更多
Trombe wall and phase change materials(PCMs)are two effective ways to regulate indoor thermal comfort.However,Trombe wall surfers from overheating in summer and PCMs suffer from low heat transfer rate caused by the li...Trombe wall and phase change materials(PCMs)are two effective ways to regulate indoor thermal comfort.However,Trombe wall surfers from overheating in summer and PCMs suffer from low heat transfer rate caused by the limited thermal conductivity.To compensate the shortcomings of the two methods,this paper proposed a Trombe wall system integrated with PCMs.Based on a light-weight building envelope in Changsha,China,the thermal comfort of 10 kinds of Trombe wall systems with PCMs with a melting temperature of 18-28℃ were studied.Taking the integrated indoor discomfort duration(I_(D)),integrated indoor discomfort degree-hour(I_(DH)),indoor air temperature(T_(in)),PCM liquid fraction(γ)and heat flux across wall(q)as evaluation indexes,the indoor thermal comfort was assessed in hot summer and cold winter region.Results show that the Trombe wall helped PCMs complete the phase change process effectively.Trombe wall with PCM25 next to the wall inner surface possessed the lowest annual I_(D) and I_(DH),as 2877 h and 12,974℃·h,respectively.Compared with the values in a traditional building,the I_(D) and I_(DH) were reduced by 7.01% and 14.14%.In order to give full play to the heat storage and heat release of the Trombe wall with PCMs,PCMs with phase change temperature 7℃ lower than the peak ambient temperature in summer or 8℃ higher than the winter night temperature was recommended according to regional climate conditions.展开更多
With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Eva...With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Evaluations based on statistical indexes(MAE,RMSE,MAPE,etc.)that characterize the accuracy of the forecasts do not help in the identification of the efficient building thermal energy demand forecast tool since they do not reflect the efforts entailed in implementation of the forecast model,i.e.,data collection to production/use phase.Hence,this work presents a Gini Index based Measurement of Alternatives and Ranking according to COmpromise Solution(GI-MARCOS),a hybrid Multi Attribute Decision Making(MADM)approach for the identification of the most efficient building energy demand forecast tool.GI-MARCOS employs(i)GI based objective weight method:assigns meaningful objective weights to the attributes in four phases(1:pre-processing,2:implementation,3:post-processing,and 4:use phase)thereby avoiding unnecessary biases in the expert’s opinion on weights and applicable to domains where there is a lack of domain expertise,and(ii)MARCOS:provides a robust and reliable ranking of alternatives in a dynamic environment.A case study with three alternatives evaluated over three to six attributes in four phases of implementation(pre-processing,implementation,post-processing and use)reveals that the use of GI-MARCOS improved the accuracy of alternatives MLR and BM by 6%and 13%,respectively.Moreover,additional validations state that(i)MLR performs best in Phase 1 and 2,while ANN performs best in Phase 3 and 4 with BM providing a mediocre performance in all four phases,(ii)sensitivity analysis:provides robust ranking with interchange of weights across phases and attributes,and(iii)rank correlation:ranks produce by GI-MARCOS has a high correlation with GRA(0.999),COPRAS(0.9786),and ARAS(0.9775).展开更多
Pre-dehumidification time(τ_(pre))and pre-dehumidification energy consumption(E_(pre))play important roles in preventing the condensation of moisture on the floors of rooms that use a radiant floor cooling(RFC)system...Pre-dehumidification time(τ_(pre))and pre-dehumidification energy consumption(E_(pre))play important roles in preventing the condensation of moisture on the floors of rooms that use a radiant floor cooling(RFC)system.However,there are few theoretical or experimental studies that focus on these two important quantities.In this study,an artificial neural network(ANN)was used to predict condensation risk for the integration of RFC systems with mixed ventilation(MV),stratum ventilation(SV),and displacement ventilation(DV)systems.A genetic algorithm-back-propagation(GA-BP)neural network model was established to predict τ_(pre) and E_(pre).Both training data and validation data were obtained from tests in a computational fluid dynamics(CFD)simulation.The results show that the established GA-BP model can predict τ_(pre) and E_(pre) well.The coefficient of determination(R^(2))of τ_(pre) and of E_(pre) were,respectively,0.973 and 0.956.For an RFC system integrated with an MV,SV,or DV system,the lowest values of τ_(pre) and E_(pre) were with the DV system,23.1 s and 0.237 kWh,respectively,for a 67.5 m^(3) room.Therefore,the best pre-dehumidification effect was with integration of the DV and RFC systems.This study showed that an ANN-based method can be used for predictive control for condensation prevention in RFC systems.It also provides a novel and effective method by which to assess the pre-dehumidification control of radiant floor surfaces.展开更多
The indoor thermal history of residents in the hot summer and cold winter climate zone in China have undergone a significant change in recent years,which also changes their seasonal thermal adaptations and this has fo...The indoor thermal history of residents in the hot summer and cold winter climate zone in China have undergone a significant change in recent years,which also changes their seasonal thermal adaptations and this has formed feed-back effects to the increasing usage of air conditioning units in this area.To study the seasonal variations of thermal adaptation,the thermal comfort experiments were conducted on two groups of participants.Each groups included 20 participants who had indoor history mainly with natural ventilation(NV group)and air-conditioning(AC group),respectively.The results demonstrated that the thermal sensation vote(TSV)in warm environments did not differ between AC and NV subjects in summer.However,the TSV of AC subjects were much lower than that of NV subjects in the same standard effective temperature and skin temperature in a cold environment in winter.Overall,the participants who spent most of their time in AC space in winter showed a low level of thermal adaptation with a narrower acceptable skin temperature range of 32.6-33.5℃.Thus,this study presents the basic information regarding the seasonal effects on human thermal adaptation due to different long-term indoor thermal histories.展开更多
This article focuses on the experimental and numerical study of an industrial prototype furnace intended for the production of ceramics in order to improve the energy efficiency and therefore optimize the fuel consump...This article focuses on the experimental and numerical study of an industrial prototype furnace intended for the production of ceramics in order to improve the energy efficiency and therefore optimize the fuel consumption and the corresponding carbon dioxide emissions.In order to understand the thermal behavior from which stems the energy efficiency of the experimental prototype,we establish in this work,a simplified modeling allowing to establish a mathematical model describing the thermal behavior of the furnace.The model is able to accurately predict the spatial and temporal distribution of the temperature at each point of the furnace to control the firing of the refractory product so that the final product is of good quality in terms of resistance and hardness.In addition,the power consumed by the prototype must be optimized in order to reduce energy and environmental consumption.In particular,this efficient technology has allowed us to save 83% of energy used in the traditional furnace and to reduce 87.36% of the relative carbon dioxide emission.The simulation of the mathematical model made it possible to compare the numerical results with the experimental measurements obtained by the prototype as well as to validate the model and to adjust the heat transfer parameters.展开更多
A novel design of Return Flow Solar Air Heater(RFSAH)with different arrangements of baffles especially V-Type Artificial roughness is simulated and numerically analyzed with energy balance equations.To enhance the eff...A novel design of Return Flow Solar Air Heater(RFSAH)with different arrangements of baffles especially V-Type Artificial roughness is simulated and numerically analyzed with energy balance equations.To enhance the effectiveness of baffles,numerous studies have been conducted.The performance of the RFSAH is studied in terms of thermal efficiency,thermo-hydraulic efficiency,and optimization of baffle parameters.Maximum Thermal efficiency and thermo-hydraulic efficiency are found in RFSAH with baffle on both sides of the absorber plate and mass flow rate above 0.2kg/s.Sensitivity analysis of the influencing parameters is carried out and reported the best performance of the system on selective geometrical parameters(ψ=0.7,β=20%,e/H=1,p/e=0.8,α=60°).The results obtained from the present model are validated with the published experimental results and have been found in quite reasonable agreement with an average error of 16.45%.Thermal and Thermohydraulic efficiency of RFSAH with a baffle on both sides of the absorber plate is maximum among baffles below,above,and on both sides of the absorber plate.It is observed that the thermal efficiency of RFSAH is greater than SF-SAH.The proposed optimum baffles roughness is suggested to increase the air upholding time period for more efficient output.展开更多
The diffusive uptake rate is essential for using passive samplers to measure indoor volatile organic compounds(VOCs).The traditional theoretical model of passive samplers requires available regression formulas of upta...The diffusive uptake rate is essential for using passive samplers to measure indoor volatile organic compounds(VOCs).The traditional theoretical model of passive samplers requires available regression formulas of uptake rates and physicochemical properties of adsorbents to predict the uptake rate.However,it is difficult to obtain the uptake rates of different VOCs under different sampling periods,and it is also difficult to obtain the physical parameters of adsorbents accurately and effectively.This study provides a reliable numerical prediction method of diffusive uptake rates of VOCs.The modeling was based on the standard automated thermal desorption(ATD)tubes packed with Tenax TA and the mass transfer process during adsorption.The experimental determinations of toluene uptake rate are carried out to verify the prediction model.Diffusive uptake rates of typical indoor VOCs are obtained from the literature to calibrate the key apparent parameters in the model by statistical regression fitting.The predicted model can provide the VOC diffusive uptake rates under different sampling duration with an average deviation of less than 5%.This study can provide the basis for fast and accurate prediction of diffusive uptake rates for various VOC pollutants in built environments.展开更多
Conventional static glazing sometimes has poor performance in energy,visual,and thermal aspects.In this thesis,a series of simulations of an office building were done to compare the performance of conventional static ...Conventional static glazing sometimes has poor performance in energy,visual,and thermal aspects.In this thesis,a series of simulations of an office building were done to compare the performance of conventional static glazing,exterior static and kinetic shades,dynamic glazing,and dynamic glazing working together with static or kinetic shades as a combinatorial system.This thesis introduced a method for designers to make decisions among multiple shading and glazing options.A scoring system was developed to evaluate the overall performance.Energy,visual and thermal performance all had the same weight.Energy uses included annual Energy Use Intensity(EUI)and peak cooling loads of the hottest day of the year.Visual performance included maximizing daylight and minimizing glare on the fall equinox day.Thermal performance included Predicted Mean Vote(PMV)Index which determined thermal comfort based on occupants’sensations and Predicted Percentage of Dissatisfied(PPD)which indicated the levels of thermal discomfort situations.The prediction was that the combination of dynamic glazing and kinetic shade would have better comprehensive performance and earn higher scores than other options.展开更多
Zero-energy buildings constitute an effective means of reducing urban carbon emissions.High airtightness,a typical characteristic of zero-energy building,is closely related to the building’s air infiltration and has ...Zero-energy buildings constitute an effective means of reducing urban carbon emissions.High airtightness,a typical characteristic of zero-energy building,is closely related to the building’s air infiltration and has a signifi-cant impact on the performance of the building envelope,indoor air quality,building energy consumption,and efficient operation of air-conditioning systems.However,thus far,systematic developments in high-airtightness assurance technologies remain scarce.Most existing studies have tested the airtightness of buildings and typical building components;however,in-depth analyses into the formation of infiltration have not been reported.There-fore,for realizing zero-energy buildings,ensuring airtightness is an urgent problem that needs to be addressed.Accordingly,in this study,based on several building airtightness measurement studies,the typical air leakage paths in buildings were summarized,and the causes of typical air leakage components in buildings were further analysed by tracing construction processes.Moreover,targeted measures for airtightness in buildings were estab-lished and applied to practical cases.Lastly,the resulting improved building airtightness was measured and the results show that the airtightness of the measured ultra-low energy consumption buildings ranges from 0.13 h^(−1)to 0.57 h^(−1),with a mean value of 0.32 h^(−1).The effectiveness of the airtightness safeguard measures was verified.This study serves as a basis for the assumption of the air leakage path distribution when simulating building air infiltration and also provides a design reference for improving the construction technologies and airtightness of buildings.展开更多
As a renewable energy source,geothermal energy has been widely used to provide space heating and cooling for buildings.The thermal performance of ground heat exchanger(GHE)is significant for the operating efficiency o...As a renewable energy source,geothermal energy has been widely used to provide space heating and cooling for buildings.The thermal performance of ground heat exchanger(GHE)is significant for the operating efficiency of the ground source heat pump(GSHP)systems.This paper presents a comprehensive review of developments and advances of three kinds of GHE,including vertical borehole GHE(VBGHE),Pile GHE(PGHE),and deep borehole GHE(DBGHE)which are currently popular in larger GSHP systems.Firstly,analytical models proposed to ana-lyze heat transfer process of VBGHE with different geological conditions are summarized,such as homogenous or heterogeneous ground,with or without groundwater advection.Numerical and short-time step models and measures to improve GHE thermal performance are also reviewed.Secondly,a summary of research advances in PGHE is provided,which includes the heat transfer models of PGHE,the effects of geometric structure,oper-ation modes,pile spacing,use of phase change material(PCM),thermal properties of PCM,thermo-mechanical behavior and/or thermal performance of PGHE.The effects of groundwater flow direction and velocity on PGHE are also summarized in brief.Lastly,models of three kinds of DBGHEs,i.e.,deep coaxial GHE(DCGHE),deep U-bend GHE(DUGHE)and super-long gravity heat pipe(SLGHP),are reviewed.The physical bases of the dif-ferent analytical models are elaborated and also their advantages and disadvantages are described.Advances in numerical modelling and improving numerical model calculation speed of DCBHE,DCBHE array,and DUBHE are summarized.The review provides a meaningful reference for the further study of GHEs.展开更多
This study examines the benefits of incorporating passive techniques into multilayer hollow clay brick walls to improve their dynamic thermal performance.The finite element approach was used to solve the incompressibl...This study examines the benefits of incorporating passive techniques into multilayer hollow clay brick walls to improve their dynamic thermal performance.The finite element approach was used to solve the incompressible Navier-Stokes and energy equations to analyze the dynamic thermal response of walls exposed to real thermal excitations of the Marrakesh climate.The results show that increasing the emissivity from 0.1 to 0.9 significantly increases the total heat load over 24 h.Furthermore,filling 100% of the cavities with insulation materials delayed the temperature peak by about 2.3 h and lowered the decrement factor by roughly 43%,with a value smaller than 0.07.In addition,it is demonstrated that the total thermal load is reduced by approximately 28% for improved wall configurations(100% insulation filling cavities)compared to traditional wall configurations(100% air filling cavities),which aids in improving building energy efficiency.展开更多
Infectious disease departments in hospitals require pressure gradient to create unidirectional airflow to prevent the spread of contaminants,typically by creating active air infiltration through the difference between...Infectious disease departments in hospitals require pressure gradient to create unidirectional airflow to prevent the spread of contaminants,typically by creating active air infiltration through the difference between supply and exhaust air volumes.The door gap is the channel of air flow between rooms,so its height has an important influence on the pressure difference and infiltration air volume of the room.There is still a lack of research on setting reasonable ventilation strategies according to the different heights of door gaps at different positions in the building.In this study,model of a set of isolation wards was established and analyzed using the multi-zone simulation software CONTAM,and the ventilation strategies with different heights of door gaps were applied to the actual infection diseases department.The results show that in a building with ventilation system divided by functional area,the difference in the height of the door gaps requires different active infiltration air volumes.Pressure fluctuations in the medical and patient corridors are greater than in other rooms.The significance of this study is to understand the active infiltration of air to guide the design and operation of ventilation systems in infectious disease hospitals or building remodeled to isolate close contacts of COVID-19 patients.It is also instructive for the design of pressure gradients in clean workshops,biological laboratories,and other similar buildings.展开更多
Due to their thermal performance,domed roofs are one of the passive solutions that affect energy consumption in buildings.The thermal performance of domed roofs has been investigated in many naturally ventilated space...Due to their thermal performance,domed roofs are one of the passive solutions that affect energy consumption in buildings.The thermal performance of domed roofs has been investigated in many naturally ventilated spaces.However,few studies have discussed their performance in conditioned spaces.Therefore,this study introduces a computational comparison between domed and flat roofs to investigate their impact on thermal comfort inside a conditioned mosque.At an earlier stage,field measurements were carried out inside a Bahraini mosque to acquire its indoor air conditions during the summer period of 2021,in addition to validating the computational model.The findings of this study confirm that,under mechanical cooling conditions,the flat roof offers a lower indoor temperature than the domed roof by 0.4℃and 0.1℃for open and closed doors,respectively.Similarly,the air velocity is lower by approximately 0.01 m/s for both door modes.The overall PMV values of the flat roof are also lower by 0.07 and 0.01,while the PPD values are lower by 0.20,and 0.34 for open and closed doors,respectively.Based on these small differences,it can be concluded that the thermal performance of both roofing systems behaves equally in conditioned spaces.However,the air patterns are substantially different,the overall thermal performance is similar.This similarity drives building designers to rethink the thermal performance of the domed roofs in air-conditioned spaces with such a hot climate,regardless of their aesthetic and acoustical behaviour.展开更多
This study aims to estimate monthly averaged daily horizontal global solar radiation.Measured climatological data collected at twelve major cities located across Libya’s map were used to establish 7 different empiric...This study aims to estimate monthly averaged daily horizontal global solar radiation.Measured climatological data collected at twelve major cities located across Libya’s map were used to establish 7 different empirical models.The empirical coefficients of the models were calculated using the least square method.The accuracy of the models was evaluated using different statistical criteria such as Taylor diagram,mean absolute percentage error,MAPE,and root mean square error,RMSE.The results indicated that the sunshine duration-based models are more accurate than air temperature-based models,and the best performance was obtained by the quadratic regression model for all twelve Libyan cities.Moreover,this regression model can be used for the prediction of monthly mean horizontal global solar radiation at a specific site across Libya’s regions with minimum error.Furthermore,the results of the global solar irradiance produced by this method can be used for designing solar systems applications.展开更多
Building-Integrated Photovoltaic(BIPV)on vertical façades is a potential PV application in today’s buildings.The performance of BIPV on façades is significantly influenced by the façade orientation.For...Building-Integrated Photovoltaic(BIPV)on vertical façades is a potential PV application in today’s buildings.The performance of BIPV on façades is significantly influenced by the façade orientation.For tropical cities,the optimum façade orientation,in terms of maximum energy yield and daylight performance,cannot be simply determined,due to relatively symmetrical sun path throughout the day.This study therefore aims to determine the optimum orientation for BIPV on tropical building façades.To achieve the objective,experiment,modelling,and computational simulation are conducted to evaluate the BIPV energy yield and to predict the indoor daylight performance in a scale-model building with a 105Wp monocrystalline silicon PV,facing each cardinal orienta-tion in Bandung,Indonesia.The South orientation yields practically zero ASE_(1000,250),providing the best annual daylight performance,and yielding the most desirable value in four out of five daylight metrics.The greatest annual energy yield is at the North orientation,providing 179-186 kWh(95%prediction interval)per year,but with larger uncertainty compared to that at the South,due to direct sunlight occurrence.Based on three different objective functions,the South orientation is considered optimum for placing the BIPV panel on the prototype façade in the location.展开更多
Internet of Things(IoT)technologies are increasingly implemented in buildings as the cost-effective smart sens-ing infrastructure of building automation systems(BASs).They are also dispersed computing resources for no...Internet of Things(IoT)technologies are increasingly implemented in buildings as the cost-effective smart sens-ing infrastructure of building automation systems(BASs).They are also dispersed computing resources for novel distributed optimal control approaches.However,wireless communication networks are critical to fulfill these tasks with the performance influenced by inherent uncertainties in networks,e.g.,unpredictable occurrence of link failures.Centralized and hierarchical distributed approaches are vulnerable against link failure,while the robustness of fully distributed approaches depends on the algorithms adopted.This study therefore proposes a fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of com-munication link in IoT-enabled BASs.The distributed algorithm is adopted that agents know their out-neighbors only.Agents directly coordinate with the connected neighbors for global optimization.Tests are conducted to test and validate the proposed approach by comparing with existing approaches,i.e.,the centralized,the hierarchical distributed and the fully distributed approaches.Results show that different approaches are vulnerable against to uncertainties of communication link to different extents.The proposed approach always guarantees the optimal control performance under normal conditions and conditions with link failures,verifying its high robustness.It also has low computation complexity and high optimization efficiency,thus applicable on IoT-enabled BASs.展开更多
The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic concerns.The purpose of the study was to investigate the influence of green industrial transformation in re...The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic concerns.The purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and 2020.Carbon emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible mediators.The association between variables is assessed using the robust least-squares approach.Green industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon emissions.The findings support the pollution haven hypothesis in a country.The causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental standards.According to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 forward.Additionally,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over time.Green industrial transitions are projected to result in a ten-year reduction in carbon emissions.The variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over time.Pakistan’s economy should foster a green industrial revolution to avoid pollution and increase environmental sustainability to meet its environmental goals.展开更多
文摘The Trombe wall is a passive indirect heating system which should be used in Cusco,Peru to improve thermal conditions against the typical frosts and low temperatures during winter in the high Andean regions.Due to this problem,the use of a modified Trombe wall with insertion of porous medium is proposed to improve thermal comfort in flat buildings in Cusco.This research aims to analyse and compare the performance of dwellings without Trombe wall,with traditional Trombe wall,and with Trombe wall with glass and plastic pellets insertion in thermal comfort improvement.Autodesk■CFD was used to simulate and analyse the system.The simulation was performed with three prototype flats(55 m^(2),75 m^(2) and 95 m^(2))for six months of the year.From the results obtained,the level of thermal comfort in the traditional scenarios is low with an average PMV of-1.86,in the scenarios with Trombe wall is good and in the scenarios with Trombe wall with insertion of porous medium is slightly better than the previous one,reaching an average PMV of+0.10 and a temperature of 21.90℃.The study carried out is important because it represents an efficient eco-sustainable heating alternative that improves the thermal comfort sensation in houses during the coldest months of the year.
文摘Advanced data mining methods have shown a promising capacity in building energy management.However,in the past decade,such methods are rarely applied in practice,since they highly rely on users to customize solutions according to the characteristics of target building energy systems.Hence,the major barrier is that the practical applications of such methods remain laborious.It is necessary to enable computers to have the human-like ability to solve data mining tasks.Generative pre-trained transformers(GPT)might be capable of addressing this issue,as some GPT models such as GPT-3.5 and GPT-4 have shown powerful abilities on interaction with humans,code generation,and inference with common sense and domain knowledge.This study explores the potential of the most advanced GPT model(GPT-4)in three data mining scenarios of building energy management,i.e.,energy load prediction,fault diagnosis,and anomaly detection.A performance evaluation framework is proposed to verify the capabilities of GPT-4 on generating energy load prediction codes,diagnosing device faults,and detecting abnormal system operation patterns.It is demonstrated that GPT-4 can automatically solve most of the data mining tasks in this domain,which overcomes the barrier of practical applications of data mining methods in this domain.In the exploration of GPT-4,its advantages and limitations are also discussed comprehensively for revealing future research directions in this domain.
文摘Due to the majority of time people spent indoors,indoor air quality is not only critical to people’s health,comfort,but can also significantly influence occupants perception on indoor environment.Air quality is closely related to many factors including thermal parameters,pollutant concentrations,and ventilation performance.However,the current building indoor air quality evaluation method is based the objective measurement of indoor parameters,without considering occupants’subjective perception.This paper is aimed at summarizing a profound review on the PAQ evaluation method.Comparisons among various PAQ evaluating methods with advantages,similarities and differences were conducted.Analysis of literatures about indoor air quality in Chinese residential buildings field is also summarized,and discussion on the subjective influence of temperature and relative humidity,venti-lation performance,volatile organic compounds(VOCs)concentration,and particulate matters on perceived air quality is carried out.
基金supported by the National Key Research and Devel-opment Program of China(2018YFE0111200)the National Natural Science Foundation of China(52078053,51608051)+4 种基金the Science and Technology Department of Hunan(2019JJ30027,2020GK4057)the Changsha City Fund for Distinguished and Innovative Young Scholars(kq2106036)the Hunan Provincial Science and Technology Depart-ment(2020WK2012,2021JJ40584)the Education Department of Hu-nan Province(19C0073)the Chenzhou Municipal Science and Tech-nology Bureau(2021SFQ01).
文摘Trombe wall and phase change materials(PCMs)are two effective ways to regulate indoor thermal comfort.However,Trombe wall surfers from overheating in summer and PCMs suffer from low heat transfer rate caused by the limited thermal conductivity.To compensate the shortcomings of the two methods,this paper proposed a Trombe wall system integrated with PCMs.Based on a light-weight building envelope in Changsha,China,the thermal comfort of 10 kinds of Trombe wall systems with PCMs with a melting temperature of 18-28℃ were studied.Taking the integrated indoor discomfort duration(I_(D)),integrated indoor discomfort degree-hour(I_(DH)),indoor air temperature(T_(in)),PCM liquid fraction(γ)and heat flux across wall(q)as evaluation indexes,the indoor thermal comfort was assessed in hot summer and cold winter region.Results show that the Trombe wall helped PCMs complete the phase change process effectively.Trombe wall with PCM25 next to the wall inner surface possessed the lowest annual I_(D) and I_(DH),as 2877 h and 12,974℃·h,respectively.Compared with the values in a traditional building,the I_(D) and I_(DH) were reduced by 7.01% and 14.14%.In order to give full play to the heat storage and heat release of the Trombe wall with PCMs,PCMs with phase change temperature 7℃ lower than the peak ambient temperature in summer or 8℃ higher than the winter night temperature was recommended according to regional climate conditions.
基金supported by The Indian Institute of Technology-Bombay(Institute Postdoctoral Fellowship-AO/Admin-1/Rect/33/2019).
文摘With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Evaluations based on statistical indexes(MAE,RMSE,MAPE,etc.)that characterize the accuracy of the forecasts do not help in the identification of the efficient building thermal energy demand forecast tool since they do not reflect the efforts entailed in implementation of the forecast model,i.e.,data collection to production/use phase.Hence,this work presents a Gini Index based Measurement of Alternatives and Ranking according to COmpromise Solution(GI-MARCOS),a hybrid Multi Attribute Decision Making(MADM)approach for the identification of the most efficient building energy demand forecast tool.GI-MARCOS employs(i)GI based objective weight method:assigns meaningful objective weights to the attributes in four phases(1:pre-processing,2:implementation,3:post-processing,and 4:use phase)thereby avoiding unnecessary biases in the expert’s opinion on weights and applicable to domains where there is a lack of domain expertise,and(ii)MARCOS:provides a robust and reliable ranking of alternatives in a dynamic environment.A case study with three alternatives evaluated over three to six attributes in four phases of implementation(pre-processing,implementation,post-processing and use)reveals that the use of GI-MARCOS improved the accuracy of alternatives MLR and BM by 6%and 13%,respectively.Moreover,additional validations state that(i)MLR performs best in Phase 1 and 2,while ANN performs best in Phase 3 and 4 with BM providing a mediocre performance in all four phases,(ii)sensitivity analysis:provides robust ranking with interchange of weights across phases and attributes,and(iii)rank correlation:ranks produce by GI-MARCOS has a high correlation with GRA(0.999),COPRAS(0.9786),and ARAS(0.9775).
基金funded by the Natural Science Foundation of Shan-dong Province(ZR2021ME199,ZR2020ME211)the Support Plan for Outstanding Youth Innovation Team in Colleges and Universities of Shandong Province(2019KJG005)supported by the Plan of Introduction and Cultivation for Young Innovative Talents in Colleges and Universities of Shandong Province.
文摘Pre-dehumidification time(τ_(pre))and pre-dehumidification energy consumption(E_(pre))play important roles in preventing the condensation of moisture on the floors of rooms that use a radiant floor cooling(RFC)system.However,there are few theoretical or experimental studies that focus on these two important quantities.In this study,an artificial neural network(ANN)was used to predict condensation risk for the integration of RFC systems with mixed ventilation(MV),stratum ventilation(SV),and displacement ventilation(DV)systems.A genetic algorithm-back-propagation(GA-BP)neural network model was established to predict τ_(pre) and E_(pre).Both training data and validation data were obtained from tests in a computational fluid dynamics(CFD)simulation.The results show that the established GA-BP model can predict τ_(pre) and E_(pre) well.The coefficient of determination(R^(2))of τ_(pre) and of E_(pre) were,respectively,0.973 and 0.956.For an RFC system integrated with an MV,SV,or DV system,the lowest values of τ_(pre) and E_(pre) were with the DV system,23.1 s and 0.237 kWh,respectively,for a 67.5 m^(3) room.Therefore,the best pre-dehumidification effect was with integration of the DV and RFC systems.This study showed that an ANN-based method can be used for predictive control for condensation prevention in RFC systems.It also provides a novel and effective method by which to assess the pre-dehumidification control of radiant floor surfaces.
基金supported by the High-end Foreign Experts Recruitment Plan of China(Grant No.G2021165006L),and the 111 Project(Grant No.B13041).
文摘The indoor thermal history of residents in the hot summer and cold winter climate zone in China have undergone a significant change in recent years,which also changes their seasonal thermal adaptations and this has formed feed-back effects to the increasing usage of air conditioning units in this area.To study the seasonal variations of thermal adaptation,the thermal comfort experiments were conducted on two groups of participants.Each groups included 20 participants who had indoor history mainly with natural ventilation(NV group)and air-conditioning(AC group),respectively.The results demonstrated that the thermal sensation vote(TSV)in warm environments did not differ between AC and NV subjects in summer.However,the TSV of AC subjects were much lower than that of NV subjects in the same standard effective temperature and skin temperature in a cold environment in winter.Overall,the participants who spent most of their time in AC space in winter showed a low level of thermal adaptation with a narrower acceptable skin temperature range of 32.6-33.5℃.Thus,this study presents the basic information regarding the seasonal effects on human thermal adaptation due to different long-term indoor thermal histories.
基金funded by a grant from Ministry of Industry of Morocco.
文摘This article focuses on the experimental and numerical study of an industrial prototype furnace intended for the production of ceramics in order to improve the energy efficiency and therefore optimize the fuel consumption and the corresponding carbon dioxide emissions.In order to understand the thermal behavior from which stems the energy efficiency of the experimental prototype,we establish in this work,a simplified modeling allowing to establish a mathematical model describing the thermal behavior of the furnace.The model is able to accurately predict the spatial and temporal distribution of the temperature at each point of the furnace to control the firing of the refractory product so that the final product is of good quality in terms of resistance and hardness.In addition,the power consumed by the prototype must be optimized in order to reduce energy and environmental consumption.In particular,this efficient technology has allowed us to save 83% of energy used in the traditional furnace and to reduce 87.36% of the relative carbon dioxide emission.The simulation of the mathematical model made it possible to compare the numerical results with the experimental measurements obtained by the prototype as well as to validate the model and to adjust the heat transfer parameters.
文摘A novel design of Return Flow Solar Air Heater(RFSAH)with different arrangements of baffles especially V-Type Artificial roughness is simulated and numerically analyzed with energy balance equations.To enhance the effectiveness of baffles,numerous studies have been conducted.The performance of the RFSAH is studied in terms of thermal efficiency,thermo-hydraulic efficiency,and optimization of baffle parameters.Maximum Thermal efficiency and thermo-hydraulic efficiency are found in RFSAH with baffle on both sides of the absorber plate and mass flow rate above 0.2kg/s.Sensitivity analysis of the influencing parameters is carried out and reported the best performance of the system on selective geometrical parameters(ψ=0.7,β=20%,e/H=1,p/e=0.8,α=60°).The results obtained from the present model are validated with the published experimental results and have been found in quite reasonable agreement with an average error of 16.45%.Thermal and Thermohydraulic efficiency of RFSAH with a baffle on both sides of the absorber plate is maximum among baffles below,above,and on both sides of the absorber plate.It is observed that the thermal efficiency of RFSAH is greater than SF-SAH.The proposed optimum baffles roughness is suggested to increase the air upholding time period for more efficient output.
基金financially supported by the National Natural Sci-ence Foundation of China(No.52078269)the special funding from Wuhan Second Ship Design and Research Institute.
文摘The diffusive uptake rate is essential for using passive samplers to measure indoor volatile organic compounds(VOCs).The traditional theoretical model of passive samplers requires available regression formulas of uptake rates and physicochemical properties of adsorbents to predict the uptake rate.However,it is difficult to obtain the uptake rates of different VOCs under different sampling periods,and it is also difficult to obtain the physical parameters of adsorbents accurately and effectively.This study provides a reliable numerical prediction method of diffusive uptake rates of VOCs.The modeling was based on the standard automated thermal desorption(ATD)tubes packed with Tenax TA and the mass transfer process during adsorption.The experimental determinations of toluene uptake rate are carried out to verify the prediction model.Diffusive uptake rates of typical indoor VOCs are obtained from the literature to calibrate the key apparent parameters in the model by statistical regression fitting.The predicted model can provide the VOC diffusive uptake rates under different sampling duration with an average deviation of less than 5%.This study can provide the basis for fast and accurate prediction of diffusive uptake rates for various VOC pollutants in built environments.
文摘Conventional static glazing sometimes has poor performance in energy,visual,and thermal aspects.In this thesis,a series of simulations of an office building were done to compare the performance of conventional static glazing,exterior static and kinetic shades,dynamic glazing,and dynamic glazing working together with static or kinetic shades as a combinatorial system.This thesis introduced a method for designers to make decisions among multiple shading and glazing options.A scoring system was developed to evaluate the overall performance.Energy,visual and thermal performance all had the same weight.Energy uses included annual Energy Use Intensity(EUI)and peak cooling loads of the hottest day of the year.Visual performance included maximizing daylight and minimizing glare on the fall equinox day.Thermal performance included Predicted Mean Vote(PMV)Index which determined thermal comfort based on occupants’sensations and Predicted Percentage of Dissatisfied(PPD)which indicated the levels of thermal discomfort situations.The prediction was that the combination of dynamic glazing and kinetic shade would have better comprehensive performance and earn higher scores than other options.
基金the Natural Science Foundation of Shandong Province Youth Project(Grant no.ZR2020QE224).
文摘Zero-energy buildings constitute an effective means of reducing urban carbon emissions.High airtightness,a typical characteristic of zero-energy building,is closely related to the building’s air infiltration and has a signifi-cant impact on the performance of the building envelope,indoor air quality,building energy consumption,and efficient operation of air-conditioning systems.However,thus far,systematic developments in high-airtightness assurance technologies remain scarce.Most existing studies have tested the airtightness of buildings and typical building components;however,in-depth analyses into the formation of infiltration have not been reported.There-fore,for realizing zero-energy buildings,ensuring airtightness is an urgent problem that needs to be addressed.Accordingly,in this study,based on several building airtightness measurement studies,the typical air leakage paths in buildings were summarized,and the causes of typical air leakage components in buildings were further analysed by tracing construction processes.Moreover,targeted measures for airtightness in buildings were estab-lished and applied to practical cases.Lastly,the resulting improved building airtightness was measured and the results show that the airtightness of the measured ultra-low energy consumption buildings ranges from 0.13 h^(−1)to 0.57 h^(−1),with a mean value of 0.32 h^(−1).The effectiveness of the airtightness safeguard measures was verified.This study serves as a basis for the assumption of the air leakage path distribution when simulating building air infiltration and also provides a design reference for improving the construction technologies and airtightness of buildings.
基金supported by the Natural Science Foundation of Shandong Province,China(ZR2020ME219)City school integration development strategy project(JNSX2021049)National Natural Science Foundation of China(No.51978599).
文摘As a renewable energy source,geothermal energy has been widely used to provide space heating and cooling for buildings.The thermal performance of ground heat exchanger(GHE)is significant for the operating efficiency of the ground source heat pump(GSHP)systems.This paper presents a comprehensive review of developments and advances of three kinds of GHE,including vertical borehole GHE(VBGHE),Pile GHE(PGHE),and deep borehole GHE(DBGHE)which are currently popular in larger GSHP systems.Firstly,analytical models proposed to ana-lyze heat transfer process of VBGHE with different geological conditions are summarized,such as homogenous or heterogeneous ground,with or without groundwater advection.Numerical and short-time step models and measures to improve GHE thermal performance are also reviewed.Secondly,a summary of research advances in PGHE is provided,which includes the heat transfer models of PGHE,the effects of geometric structure,oper-ation modes,pile spacing,use of phase change material(PCM),thermal properties of PCM,thermo-mechanical behavior and/or thermal performance of PGHE.The effects of groundwater flow direction and velocity on PGHE are also summarized in brief.Lastly,models of three kinds of DBGHEs,i.e.,deep coaxial GHE(DCGHE),deep U-bend GHE(DUGHE)and super-long gravity heat pipe(SLGHP),are reviewed.The physical bases of the dif-ferent analytical models are elaborated and also their advantages and disadvantages are described.Advances in numerical modelling and improving numerical model calculation speed of DCBHE,DCBHE array,and DUBHE are summarized.The review provides a meaningful reference for the further study of GHEs.
文摘This study examines the benefits of incorporating passive techniques into multilayer hollow clay brick walls to improve their dynamic thermal performance.The finite element approach was used to solve the incompressible Navier-Stokes and energy equations to analyze the dynamic thermal response of walls exposed to real thermal excitations of the Marrakesh climate.The results show that increasing the emissivity from 0.1 to 0.9 significantly increases the total heat load over 24 h.Furthermore,filling 100% of the cavities with insulation materials delayed the temperature peak by about 2.3 h and lowered the decrement factor by roughly 43%,with a value smaller than 0.07.In addition,it is demonstrated that the total thermal load is reduced by approximately 28% for improved wall configurations(100% insulation filling cavities)compared to traditional wall configurations(100% air filling cavities),which aids in improving building energy efficiency.
文摘Infectious disease departments in hospitals require pressure gradient to create unidirectional airflow to prevent the spread of contaminants,typically by creating active air infiltration through the difference between supply and exhaust air volumes.The door gap is the channel of air flow between rooms,so its height has an important influence on the pressure difference and infiltration air volume of the room.There is still a lack of research on setting reasonable ventilation strategies according to the different heights of door gaps at different positions in the building.In this study,model of a set of isolation wards was established and analyzed using the multi-zone simulation software CONTAM,and the ventilation strategies with different heights of door gaps were applied to the actual infection diseases department.The results show that in a building with ventilation system divided by functional area,the difference in the height of the door gaps requires different active infiltration air volumes.Pressure fluctuations in the medical and patient corridors are greater than in other rooms.The significance of this study is to understand the active infiltration of air to guide the design and operation of ventilation systems in infectious disease hospitals or building remodeled to isolate close contacts of COVID-19 patients.It is also instructive for the design of pressure gradients in clean workshops,biological laboratories,and other similar buildings.
文摘Due to their thermal performance,domed roofs are one of the passive solutions that affect energy consumption in buildings.The thermal performance of domed roofs has been investigated in many naturally ventilated spaces.However,few studies have discussed their performance in conditioned spaces.Therefore,this study introduces a computational comparison between domed and flat roofs to investigate their impact on thermal comfort inside a conditioned mosque.At an earlier stage,field measurements were carried out inside a Bahraini mosque to acquire its indoor air conditions during the summer period of 2021,in addition to validating the computational model.The findings of this study confirm that,under mechanical cooling conditions,the flat roof offers a lower indoor temperature than the domed roof by 0.4℃and 0.1℃for open and closed doors,respectively.Similarly,the air velocity is lower by approximately 0.01 m/s for both door modes.The overall PMV values of the flat roof are also lower by 0.07 and 0.01,while the PPD values are lower by 0.20,and 0.34 for open and closed doors,respectively.Based on these small differences,it can be concluded that the thermal performance of both roofing systems behaves equally in conditioned spaces.However,the air patterns are substantially different,the overall thermal performance is similar.This similarity drives building designers to rethink the thermal performance of the domed roofs in air-conditioned spaces with such a hot climate,regardless of their aesthetic and acoustical behaviour.
文摘This study aims to estimate monthly averaged daily horizontal global solar radiation.Measured climatological data collected at twelve major cities located across Libya’s map were used to establish 7 different empirical models.The empirical coefficients of the models were calculated using the least square method.The accuracy of the models was evaluated using different statistical criteria such as Taylor diagram,mean absolute percentage error,MAPE,and root mean square error,RMSE.The results indicated that the sunshine duration-based models are more accurate than air temperature-based models,and the best performance was obtained by the quadratic regression model for all twelve Libyan cities.Moreover,this regression model can be used for the prediction of monthly mean horizontal global solar radiation at a specific site across Libya’s regions with minimum error.Furthermore,the results of the global solar irradiance produced by this method can be used for designing solar systems applications.
基金supported by the Ministry of Education,Culture,Research,and Technology of the Republic of Indonesia,through the In-donesia Collaboration Research Program(RKI)2022.
文摘Building-Integrated Photovoltaic(BIPV)on vertical façades is a potential PV application in today’s buildings.The performance of BIPV on façades is significantly influenced by the façade orientation.For tropical cities,the optimum façade orientation,in terms of maximum energy yield and daylight performance,cannot be simply determined,due to relatively symmetrical sun path throughout the day.This study therefore aims to determine the optimum orientation for BIPV on tropical building façades.To achieve the objective,experiment,modelling,and computational simulation are conducted to evaluate the BIPV energy yield and to predict the indoor daylight performance in a scale-model building with a 105Wp monocrystalline silicon PV,facing each cardinal orienta-tion in Bandung,Indonesia.The South orientation yields practically zero ASE_(1000,250),providing the best annual daylight performance,and yielding the most desirable value in four out of five daylight metrics.The greatest annual energy yield is at the North orientation,providing 179-186 kWh(95%prediction interval)per year,but with larger uncertainty compared to that at the South,due to direct sunlight occurrence.Based on three different objective functions,the South orientation is considered optimum for placing the BIPV panel on the prototype façade in the location.
基金supported by a collaborative research fund(C5018-20G)of the Research Grant Council(RGC)of the Hong Kong SAR and a project of strategic importance of The Hong Kong Poly-technic University.
文摘Internet of Things(IoT)technologies are increasingly implemented in buildings as the cost-effective smart sens-ing infrastructure of building automation systems(BASs).They are also dispersed computing resources for novel distributed optimal control approaches.However,wireless communication networks are critical to fulfill these tasks with the performance influenced by inherent uncertainties in networks,e.g.,unpredictable occurrence of link failures.Centralized and hierarchical distributed approaches are vulnerable against link failure,while the robustness of fully distributed approaches depends on the algorithms adopted.This study therefore proposes a fully distributed robust optimal control approach for air-conditioning systems considering uncertainties of com-munication link in IoT-enabled BASs.The distributed algorithm is adopted that agents know their out-neighbors only.Agents directly coordinate with the connected neighbors for global optimization.Tests are conducted to test and validate the proposed approach by comparing with existing approaches,i.e.,the centralized,the hierarchical distributed and the fully distributed approaches.Results show that different approaches are vulnerable against to uncertainties of communication link to different extents.The proposed approach always guarantees the optimal control performance under normal conditions and conditions with link failures,verifying its high robustness.It also has low computation complexity and high optimization efficiency,thus applicable on IoT-enabled BASs.
文摘The industrial sector is vital to economic progress,yet industrial pollution poses environmental and economic concerns.The purpose of the study was to investigate the influence of green industrial transformation in re-ducing Pakistan’s carbon intensity between 1975 and 2020.Carbon emissions are considered an endogenous construct,while foreign direct investment(FDI)inflows,technological innovation,green industrial transforma-tion,environmental legislation,and research and development(R&D)investment are possible mediators.The association between variables is assessed using the robust least-squares approach.Green industrial transforma-tion is connected with lower carbon emissions,yet technical innovation,R&D investment,and inbound FDI raise a country’s carbon emissions.The findings support the pollution haven hypothesis in a country.The causality esti-mates indicate that inward FDI contributes to environmental regulations;green industrial transformation directly relates to inbound FDI and R&D expenditures;and technological innovations correspond to inbound FDI,R&D ex-penditures,industrial ecofriendly progression,and environmental standards.According to the impulse response function,environmental policies are anticipated to have a differential effect on carbon emissions in 2023,2024,2028-2030,while they are likely to decrease in the years 2025-2027 and 2031 forward.Additionally,inward FDI and technology advancements would almost certainly result in a rise in carbon emissions over time.Green industrial transitions are projected to result in a ten-year reduction in carbon emissions.The variance decomposi-tion analysis indicates that eco-friendly industrial adaptations would likely have the largest variance error shock on carbon emissions(11.747%),followed by inbound FDI,technological advancements,and regulatory changes,with R&D spending having a minimal impact over time.Pakistan’s economy should foster a green industrial revolution to avoid pollution and increase environmental sustainability to meet its environmental goals.
