A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters (e.g. air temperatur...A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters (e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the prediction of thaw depths in Fairbanks, Alaska, is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters, and temperature data can lead to significant uncertainty in predicting thaw penetration. The Taylor series method was performed to determine the mean and standard deviation of thaw penetration and the results were compared to the Monte Carlo simulation results. The close comparison of the results suggests that the simpler Taylor series method may be applied to many cold regions problems to account for the variability of input parameters.展开更多
Sediment cores, suspended particles and overlying water were collected in Deep Bay, Hong Kong. Enrichment of Zn in surface sediments in the landward direction and the decreasing of exchangeable Cd, Ni and Zn in sedime...Sediment cores, suspended particles and overlying water were collected in Deep Bay, Hong Kong. Enrichment of Zn in surface sediments in the landward direction and the decreasing of exchangeable Cd, Ni and Zn in sediment from the inner bay to the outer bay indicated the influence of anthropogenic pollutants discharged from the riparian runoffs.展开更多
An aerobic bacterium strain, F-3-4, capable of effectively degrading 2,6-di-tert-butylphenol(2,6-DTBP), was isolated and screened out from an acrylic fiber wastewater and the biofilm in the wastewater treatment facili...An aerobic bacterium strain, F-3-4, capable of effectively degrading 2,6-di-tert-butylphenol(2,6-DTBP), was isolated and screened out from an acrylic fiber wastewater and the biofilm in the wastewater treatment facilities. This strain was identified as Alcaligenes sp. through morphological, physiological and biochemical examinations. After cultivation, the strain was enhanced by 26.3% in its degradation capacity for 2,6-DTBP. Results indicated that the strain was able to utilize 2,6-DTBP, lysine, lactamine, citrate, n-utenedioic acid and malic acid as the sole carbon and energy source, alkalinize acetamide, asparagine, L-histidine, acetate, citrate and propionate, but failed to utilize glucose, D-fructose, D-seminose, D-xylose, serine and phenylalanine as the sole carbon and energy source. The optimal growth conditions were determined to be: temperature 37℃, pH 7.0, inoculum size 0.1% and shaker rotary speed 250 r/min. Under the optimal conditions, the degradation kinetics of 2,6-DTBP with an initial concentration of 100 mg/L was studied. Results indicated that 62.4% of 2,6-DTBP was removed after 11 d. The degradation kinetics could be expressed by Eckenfelder equation with a half life of 9.38 d. In addition, the initial concentration of 2,6-DTBP played an important role on the degradation ability of the strain. The maximum initial concentration of 2,6-DTBP was determined to be 200 mg/L. Above this level, the strain was overloaded and exhibited significant inhibition.展开更多
The need to provide efficient public transport services in urban areas has led to the implementation of bus priority measures in many congested cities. Much interest has recently centred on priority at signal controll...The need to provide efficient public transport services in urban areas has led to the implementation of bus priority measures in many congested cities. Much interest has recently centred on priority at signal controlled junctions, including the concept of pre-signals, where traffic signals are installed at or near the end of a with-flow bus lane to provide buses with priority access to the downstream junction. Although a number of pre-signals have now been installed in the UK, particularly in London, there has been very little published research into the analysis of benefits and disbenefits to both buses and non-priority vehicles at pre-signalised intersections.This paper addresses these points through the development of analytical procedures which allow pre-implementation evaluation of specific categories of pre-signals.展开更多
Energy demand fluctuations due to low probability high impact(LPHI)micro-climatic events such as urban heat island effect(UHI)and heatwaves,pose significant challenges for urban infrastructure,particularly within urba...Energy demand fluctuations due to low probability high impact(LPHI)micro-climatic events such as urban heat island effect(UHI)and heatwaves,pose significant challenges for urban infrastructure,particularly within urban built-clusters.Mapping short term load forecasting(STLF)of buildings in urban micro-climatic setting(UMS)is obscured by the complex interplay of surrounding morphology,micro-climate and inter-building energy dynamics.Conventional urban building energy modelling(UBEM)approaches to provide quantitative insights about building energy consumption often neglect the synergistic impacts of micro-climate and urban morphology in short temporal scale.Reduced order modelling,unavailability of rich urban datasets such as building key performance indicators for building archetypes-characterization,limit the inter-building energy dynamics consideration into UBEMs.In addition,mismatch of resolutions of spatio-temporal datasets(meso to micro scale transition),LPHI events extent prediction around UMS as well as its accurate quantitative inclusion in UBEM input organization step pose another degree of limitations.This review aims to direct attention towards an integrated-UBEM(i-UBEM)framework to capture the building load fluctuation over multi-scale spatio–temporal scenario.It highlights usage of emerging data-driven hybrid approaches,after systematically analysing developments and limitations of recent physical,data-driven artificial intelligence and machine learning(AI-ML)based modelling approaches.It also discusses the potential integration of google earth engine(GEE)-cloud computing platform in UBEM input organization step to(i)map the land surface temperature(LST)data(quantitative attribute implying LPHI event occurrence),(ii)manage and pre-process high-resolution spatio-temporal UBEM input-datasets.Further the potential of digital twin,central structed data models to integrate along UBEM workflow to reduce uncertainties related to building archetype characterizations is explored.It has also found that a trade-off between high-fidelity baseline simulation models and computationally efficient platform support or co-simulation platform integration is essential to capture LPHI induced inter-building energy dynamics.展开更多
文摘A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters (e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the prediction of thaw depths in Fairbanks, Alaska, is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters, and temperature data can lead to significant uncertainty in predicting thaw penetration. The Taylor series method was performed to determine the mean and standard deviation of thaw penetration and the results were compared to the Monte Carlo simulation results. The close comparison of the results suggests that the simpler Taylor series method may be applied to many cold regions problems to account for the variability of input parameters.
文摘Sediment cores, suspended particles and overlying water were collected in Deep Bay, Hong Kong. Enrichment of Zn in surface sediments in the landward direction and the decreasing of exchangeable Cd, Ni and Zn in sediment from the inner bay to the outer bay indicated the influence of anthropogenic pollutants discharged from the riparian runoffs.
文摘An aerobic bacterium strain, F-3-4, capable of effectively degrading 2,6-di-tert-butylphenol(2,6-DTBP), was isolated and screened out from an acrylic fiber wastewater and the biofilm in the wastewater treatment facilities. This strain was identified as Alcaligenes sp. through morphological, physiological and biochemical examinations. After cultivation, the strain was enhanced by 26.3% in its degradation capacity for 2,6-DTBP. Results indicated that the strain was able to utilize 2,6-DTBP, lysine, lactamine, citrate, n-utenedioic acid and malic acid as the sole carbon and energy source, alkalinize acetamide, asparagine, L-histidine, acetate, citrate and propionate, but failed to utilize glucose, D-fructose, D-seminose, D-xylose, serine and phenylalanine as the sole carbon and energy source. The optimal growth conditions were determined to be: temperature 37℃, pH 7.0, inoculum size 0.1% and shaker rotary speed 250 r/min. Under the optimal conditions, the degradation kinetics of 2,6-DTBP with an initial concentration of 100 mg/L was studied. Results indicated that 62.4% of 2,6-DTBP was removed after 11 d. The degradation kinetics could be expressed by Eckenfelder equation with a half life of 9.38 d. In addition, the initial concentration of 2,6-DTBP played an important role on the degradation ability of the strain. The maximum initial concentration of 2,6-DTBP was determined to be 200 mg/L. Above this level, the strain was overloaded and exhibited significant inhibition.
文摘The need to provide efficient public transport services in urban areas has led to the implementation of bus priority measures in many congested cities. Much interest has recently centred on priority at signal controlled junctions, including the concept of pre-signals, where traffic signals are installed at or near the end of a with-flow bus lane to provide buses with priority access to the downstream junction. Although a number of pre-signals have now been installed in the UK, particularly in London, there has been very little published research into the analysis of benefits and disbenefits to both buses and non-priority vehicles at pre-signalised intersections.This paper addresses these points through the development of analytical procedures which allow pre-implementation evaluation of specific categories of pre-signals.
基金the Sponsored Research and Industrial Consultancy(SRIC)grant No:IIT/SRIC/AR/MWS/2021-2022/057the SERB grant No.IPA/2021/000081.
文摘Energy demand fluctuations due to low probability high impact(LPHI)micro-climatic events such as urban heat island effect(UHI)and heatwaves,pose significant challenges for urban infrastructure,particularly within urban built-clusters.Mapping short term load forecasting(STLF)of buildings in urban micro-climatic setting(UMS)is obscured by the complex interplay of surrounding morphology,micro-climate and inter-building energy dynamics.Conventional urban building energy modelling(UBEM)approaches to provide quantitative insights about building energy consumption often neglect the synergistic impacts of micro-climate and urban morphology in short temporal scale.Reduced order modelling,unavailability of rich urban datasets such as building key performance indicators for building archetypes-characterization,limit the inter-building energy dynamics consideration into UBEMs.In addition,mismatch of resolutions of spatio-temporal datasets(meso to micro scale transition),LPHI events extent prediction around UMS as well as its accurate quantitative inclusion in UBEM input organization step pose another degree of limitations.This review aims to direct attention towards an integrated-UBEM(i-UBEM)framework to capture the building load fluctuation over multi-scale spatio–temporal scenario.It highlights usage of emerging data-driven hybrid approaches,after systematically analysing developments and limitations of recent physical,data-driven artificial intelligence and machine learning(AI-ML)based modelling approaches.It also discusses the potential integration of google earth engine(GEE)-cloud computing platform in UBEM input organization step to(i)map the land surface temperature(LST)data(quantitative attribute implying LPHI event occurrence),(ii)manage and pre-process high-resolution spatio-temporal UBEM input-datasets.Further the potential of digital twin,central structed data models to integrate along UBEM workflow to reduce uncertainties related to building archetype characterizations is explored.It has also found that a trade-off between high-fidelity baseline simulation models and computationally efficient platform support or co-simulation platform integration is essential to capture LPHI induced inter-building energy dynamics.
