In the context of advancing towards dual carbon goals,numerous factories are actively engaging in energy efficiency upgrades and transformations.To accurately pinpoint energy efficiency bottlenecks within factories an...In the context of advancing towards dual carbon goals,numerous factories are actively engaging in energy efficiency upgrades and transformations.To accurately pinpoint energy efficiency bottlenecks within factories and prioritize renovation sequences,it is crucial to conduct comprehensive evaluations of the energy performance across various workshops.Therefore,this paper proposes an evaluation model for workshop energy efficiency based on the drive-state-response(DSR)framework combined with the fuzzy BORDA method.Firstly,an in-depth analysis of the relationships between different energy efficiency indicators was conducted.Based on the DSR model,evaluation criteria were selected from three dimensions-drive factors,state characteristics,and response measures-to establish a robust energy efficiency indicator system.Secondly,three distinct assessment techniques were selected:Grey Relational Analysis(GRA),Entropy Weight Method(EWM),and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)forming a diversified set of evaluation methods.Subsequently,by introducing the fuzzy BORDA method,a comprehensive energy efficiency evaluation model was developed,aimed at quantitatively ranking the energy performance status of each workshop.Using a real-world factory as a case study,applying our proposed evaluationmodel yielded detailed scores and rankings for each workshop.Furthermore,post hoc testing was performed using the Spearman correlation coefficient,revealing a statistic value of 10.209,which validates the effectiveness and reliability of the proposed evaluation model.This model not only assists in identifying underperforming workshops within the factory but also provides solid data support and a decision-making basis for future energy efficiency optimization strategies.展开更多
Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring...Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring their functional integrity and performance.To achieve sustainable manufacturing in FDM,it is necessary to optimize the print quality and time efficiency concurrently.However,owing to the complex interactions of printing parameters,achieving a balanced optimization of both remains challenging.This study examines four key factors affecting dimensional accuracy and print time:printing speed,layer thickness,nozzle temperature,and bed temperature.Fifty parameter sets were generated using enhanced Latin hypercube sampling.A whale optimization algorithm(WOA)-enhanced support vector regression(SVR)model was developed to predict dimen-sional errors and print time effectively,with non-dominated sorting genetic algorithm Ⅲ(NSGA-Ⅲ)utilized for multi-objective optimization.The technique for Order Preference by Similarity to Ideal Solution(TOPSIS)was applied to select a balanced solution from the Pareto front.In experimental validation,the parts printed using the optimized parameters exhibited excellent dimensional accuracy and printing efficiency.This study comprehensively considered optimizing the printing time and size to meet quality requirements while achieving higher printing efficiency and aiding in the realization of sustainable manufacturing in the field of AM.In addition,the printing of a specific prosthetic component was used as a case study,highlighting the high demands on both dimensional precision and printing efficiency.The optimized process parameters required significantly less printing time,while satisfying the dimensional accuracy requirements.This study provides valuable insights for achieving sustainable AM using FDM.展开更多
Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still...Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.展开更多
This research investigates the influence of indoor and outdoor factors on photovoltaic(PV)power generation at Utrecht University to accurately predict PV system performance by identifying critical impact factors and i...This research investigates the influence of indoor and outdoor factors on photovoltaic(PV)power generation at Utrecht University to accurately predict PV system performance by identifying critical impact factors and improving renewable energy efficiency.To predict plant efficiency,nineteen variables are analyzed,consisting of nine indoor photovoltaic panel characteristics(Open Circuit Voltage(Voc),Short Circuit Current(Isc),Maximum Power(Pmpp),Maximum Voltage(Umpp),Maximum Current(Impp),Filling Factor(FF),Parallel Resistance(Rp),Series Resistance(Rs),Module Temperature)and ten environmental factors(Air Temperature,Air Humidity,Dew Point,Air Pressure,Irradiation,Irradiation Propagation,Wind Speed,Wind Speed Propagation,Wind Direction,Wind Direction Propagation).This study provides a new perspective not previously addressed in the literature.In this study,different machine learning methods such as Multilayer Perceptron(MLP),Multivariate Adaptive Regression Spline(MARS),Multiple Linear Regression(MLR),and Random Forest(RF)models are used to predict power values using data from installed PVpanels.Panel values obtained under real field conditions were used to train the models,and the results were compared.The Multilayer Perceptron(MLP)model was achieved with the highest classification accuracy of 0.990%.The machine learning models used for solar energy forecasting show high performance and produce results close to actual values.Models like Multi-Layer Perceptron(MLP)and Random Forest(RF)can be used in diverse locations based on load demand.展开更多
Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes...Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.展开更多
The efficiency of particle screening was studied over a range of vibrational parameters including amplitude, frequency and vibrational direction. The Discrete Element Method (DEM) was used to simulate the screening pr...The efficiency of particle screening was studied over a range of vibrational parameters including amplitude, frequency and vibrational direction. The Discrete Element Method (DEM) was used to simulate the screening process. A functional relationship between efficiency and the parameters, both singly and combined, is established. The function is a complicated exponential. Optimal amplitude and frequency values are smaller for particles near the mesh and larger for other particles. The optimum vibration angle is 45° for nearly all kinds of particles. A transverse velocity, V⊥, was defined and V⊥=0.2 m/s was identified to be the most efficient operating point by both simulation and experimental observation. Comparison of these results with those reported by others is included.展开更多
Earlier investigators have numerically carried out performance analysis of the invert trap fitted in an open channel using the stochastic discrete phase model(DPM) by assuming the open channel flow to be closed condui...Earlier investigators have numerically carried out performance analysis of the invert trap fitted in an open channel using the stochastic discrete phase model(DPM) by assuming the open channel flow to be closed conduit flow under pressure and assuming zero shear stress at the top wall.This is known as the fixed lid model.By assuming the top wall to be a shear free wall,they have been able to show that the velocity distribution looks similar to that of an open channel flow with zero velocity at the bottom and maximum velocity at the top,representing the free water surface,but no information has been provided for the pressure at the free water surface.Because of this assumption,the validation of the model in predicting the trap efficiency has performed significantly poorly.In addition,the free water surface subject to zero gauge pressure cannot be modeled using the fixed lid model because there is no provision of extra space in the form of air space for the fluctuating part of the water surface profile.It can.however,be modeled using the volume of fluid(VOF) model because the VOF model is the appropriate model for open channel or free surface flow.Therefore,in the present study,three-dimensional(3D) computational fluid dynamics(CFD) modeling with the VOF model,which considers open channel flow with a free water surface,along with the stochastic DPM.was used to model the trap efficiency of an invert trap fitted in an open rectangular channel.The governing mathematical flow equations of the VOF model were solved using the ANSYS Fluent 14.0 software,reproducing the experimental conditions exactly.The results show that the 3D CFD predictions using the VOF model closely fit the experimental data for glass bead particles.展开更多
Two-oriented agriculture was a complex organism coupling production,economics,society and ecology.Its development process was affected by various factors such as producers,nature,society,etc.In order to overcome measu...Two-oriented agriculture was a complex organism coupling production,economics,society and ecology.Its development process was affected by various factors such as producers,nature,society,etc.In order to overcome measurement error of traditional data envelopment analysis caused by ignoring random,three-stage DEA model was studied to remove environmental factors and random effects.On the foundation of this model was two-oriented agriculture comprehensive production efficiency of 14 cities were estimated in Hunan Province in 2008,and brown forth corresponding policy proposals to promote agricultural development.展开更多
The efficiency of any energy system can be charaterised by the relevant efficiency components in terms of performance, operation, equipment and technology(POET). The overall energy efficiency of the system can be opti...The efficiency of any energy system can be charaterised by the relevant efficiency components in terms of performance, operation, equipment and technology(POET). The overall energy efficiency of the system can be optimised by studying the POET energy efficiency components. For an existing energy system, the improvement of operation efficiency will usually be a quick win for energy efficiency. Therefore, operation efficiency improvement will be the main purpose of this paper. General procedures to establish operation efficiency optimisation models are presented. Model predictive control, a popular technique in modern control theory, is applied to solve the obtained energy models. From the case studies in water pumping systems, model predictive control will have a prosperous application in more energy efficiency problems.展开更多
This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient ou...This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.展开更多
Adopting a soft site model built on soft interlayer soil foundation,a shaking table test for soft interlayer soil-isolated structure interaction is conducted to investigate the seismic response of isolated structure o...Adopting a soft site model built on soft interlayer soil foundation,a shaking table test for soft interlayer soil-isolated structure interaction is conducted to investigate the seismic response of isolated structure on soft site,and analyze its isolation effect.Test results show that the test can reflect the earthquake response characteristics of isolated structure on soft site.It is on soft site that the dynamic characteristics of isolated structure,acceleration magnification factor(AMF)of isolated structure and isolation efficiency of the isolation layer differ from those on rigid foundation with an soil-structure interaction(SSI)effect,represented by the reduction in fundamental vibration frequency of isolated structure and the increase of damping ratio with changes of the SSI effect.SSI can either increase or decrease AMF of isolated structure on soft site,depending on the characteristics of earthquake motion input.Furthermore,the isolation efficiency of isolation layer on soft site is decreased with the SSI effect,which is related to the peak ground acceleration(PGA)and the characteristics of earthquake motion input.展开更多
Using a heterogeneity stochastic frontier model(HSFM),we empirically investigated the economic efficiency of Beijing-Tianjin-Hebei from 2003 to 2016 and its influencing factors.The key findings of the paper lie in:1)i...Using a heterogeneity stochastic frontier model(HSFM),we empirically investigated the economic efficiency of Beijing-Tianjin-Hebei from 2003 to 2016 and its influencing factors.The key findings of the paper lie in:1)in Beijing-Tianjin-Hebei,the overall economic and technological efficiency tended to increase in a wavelike manner,economic growth slowed down,and there was an obvious imbalance in economic efficiency between the different districts,counties and cities;2)the heterogeneity stochastic frontier production functions(SFPFs)of Beijing,Tianjin and Hebei were different from each other,and investment was still an important impetus of economic growth in Beijing-Tianjin-Hebei;3)economic efficiency was positively correlated with economic agglomeration,human capital,industrial structure,infrastructure,the informatization level,and institutional factors,but negatively correlated with the government role and economic opening.The following policy suggestions are offered:1)to improve regional economic efficiency and reduce the economic gap in Beijing-Tianjin-Hebei,governments must reduce their intervention in economic activities,stimulate the potentials of labor and capital,optimize the structure of human resources,and foster new demographic incentives;2)governments must guide economic factors that are reasonable throughout Beijing-Tianjin-Hebei and strengthen infrastructure construction in underdeveloped regions,thus attaining sustainable economic development;3)governments must plan overall economic growth factors of Beijing-Tianjin-Hebei and promote reasonable economic factors(e.g.,labor,resources,and innovations)across different regions,thus attaining complementary advantages between Beijing,Tianjin,and Hebei.展开更多
This research appraises comparative analysis between single diode and double diode model of photovoltaic (PV) solar cells to enhance the conversion efficiency of power engendering PV solar systems. Single diode model ...This research appraises comparative analysis between single diode and double diode model of photovoltaic (PV) solar cells to enhance the conversion efficiency of power engendering PV solar systems. Single diode model is simple and easy to implement, whereas double diode model has better accuracy which acquiesces for more precise forecast of PV systems performance. Exploration is done on the basis of simulation results and MATLAB tool is used to serve this purpose. Simulations are performed by varying distinct model parameters such as solar irradiance, temperature, value of parasitic resistances, ideality factor of diode and number of series and parallel connected solar cells used to assemble PV array. Conspicuous demonstration is executed to analyze effects of these specifications on the efficiency curve and power vs. voltage output characteristics of PV cell for specified models.展开更多
Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at p...Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at present, the C2R model and the C2GS2 model have limitations when used alone,resulting in evaluations that are often unsatisfactory. In order to solve this problem, a mixed DEA model is built and is used to evaluate the validity of the business efficiency of listed companies. An explanation of how to use this mixed DEA model is offered and its feasibility is verified.展开更多
Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the ...Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.展开更多
The front-row shading reduction coefficient is a key parameter used to calculate the system efficiency of a photovoltaic(PV)power station.Based on the Hay anisotropic sky scattering model,the variation rule of solar r...The front-row shading reduction coefficient is a key parameter used to calculate the system efficiency of a photovoltaic(PV)power station.Based on the Hay anisotropic sky scattering model,the variation rule of solar radiation intensity on the surface of the PV array during the shaded period is simulated,combined with the voltage-current characteristics of the PV modules,and the shadow occlusion operating mode of the PV array is modeled.A method for calculating the loss coefficient of front shadow occlusion based on the division of the PV cell string unit and Hay anisotropic sky scattering model is proposed.This algorithm can accurately evaluate the degree of influence of the PV array layout,wiring mode,array spacing,PV module specifications,and solar radiation on PV power station system efficiency.It provides a basis for optimizing the PV array layout,reducing system loss,and improving PV system efficiency.展开更多
Bohai Rim region is an important economic development area and a large carbon emission area in China.It is of great significance to explore the total factor energy efficiency and its influencing factors for the low ca...Bohai Rim region is an important economic development area and a large carbon emission area in China.It is of great significance to explore the total factor energy efficiency and its influencing factors for the low carbon transformation and high-quality development of the Bohai Rim region.Based on the total factor energy efficiency framework,the DDF-DEA model was used to calculate the total factor energy efficiency,and the internal and external differences of the total factor energy efficiency were further analyzed.The internal and external influencing factors were determined by ML index method and classical endogenous growth theory,and then the Tobit panel model was used to empirically analyze the action mechanism of all influencing factors of total factor energy efficiency in the Bohai Rim region.The results show that the pure technical efficiency,scale efficiency and technological progress among the internal influencing factors contribute to the improvement of energy efficiency in the Bohai Rim region.Industrial structure,industrial internal structure and ownership structure inhibit the improvement of energy efficiency.Energy consumption structure and energy endowment also have a negative impact on energy efficiency.Therefore,measures such as promoting technological progress,adjusting economic structure and optimizing energy structure will effectively improve total factor energy efficiency in the Bohai Rim region.展开更多
Because of ground clutter wave interf e rence,it is difficult to measure smoke screen disturbance in the field.In this pape r,a kind of indoor measurement method of smoke screen disturbance efficiency ba sed on Gaussi...Because of ground clutter wave interf e rence,it is difficult to measure smoke screen disturbance in the field.In this pape r,a kind of indoor measurement method of smoke screen disturbance efficiency ba sed on Gaussian diffusion model is put forward.As a characteristic,the measur ement result of smoke screen area density proves that the indoor measurement met hod of smoke screen disturbance efficiency based on Gaussian diffusion model is fea sible.展开更多
Applying the slacks-based measure （SBM）-Tobit two-stage model, this paper analyzes energy efficiency in eastern China. First, the SBM model featured in taking non- desired output in calculation was employed to evalu...Applying the slacks-based measure （SBM）-Tobit two-stage model, this paper analyzes energy efficiency in eastern China. First, the SBM model featured in taking non- desired output in calculation was employed to evaluate the energy efficiency in eastern China from 1995 to 2010. The results show that Tianjin, Shanghai and Guangdong have the highest energy efficiency while Hebei has the lowest. Next, we used the panel Tobit model to perform a regression on factors affecting energy efficiency. Our results show that optimizing industrial structure, improving energy structure and enhancing the level of economic reform can contribute to improving energy efficiency. Government influence and technological progress, on the other hand, affect energy efficiency insignificantly. The influence of socio-economic development on the energy efficiency goes from negative to positive, which adheres to the Kuznets curve hypothesis. Our findings are that the socio-economic development in eastern China has not yet passed the ＂turning point of the Kuznets curve ＂.展开更多
基金funded by the National Social Science Fund of China(Grant No.23BGL234).
文摘In the context of advancing towards dual carbon goals,numerous factories are actively engaging in energy efficiency upgrades and transformations.To accurately pinpoint energy efficiency bottlenecks within factories and prioritize renovation sequences,it is crucial to conduct comprehensive evaluations of the energy performance across various workshops.Therefore,this paper proposes an evaluation model for workshop energy efficiency based on the drive-state-response(DSR)framework combined with the fuzzy BORDA method.Firstly,an in-depth analysis of the relationships between different energy efficiency indicators was conducted.Based on the DSR model,evaluation criteria were selected from three dimensions-drive factors,state characteristics,and response measures-to establish a robust energy efficiency indicator system.Secondly,three distinct assessment techniques were selected:Grey Relational Analysis(GRA),Entropy Weight Method(EWM),and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)forming a diversified set of evaluation methods.Subsequently,by introducing the fuzzy BORDA method,a comprehensive energy efficiency evaluation model was developed,aimed at quantitatively ranking the energy performance status of each workshop.Using a real-world factory as a case study,applying our proposed evaluationmodel yielded detailed scores and rankings for each workshop.Furthermore,post hoc testing was performed using the Spearman correlation coefficient,revealing a statistic value of 10.209,which validates the effectiveness and reliability of the proposed evaluation model.This model not only assists in identifying underperforming workshops within the factory but also provides solid data support and a decision-making basis for future energy efficiency optimization strategies.
基金supporteded by Natural Science Foundation of Shanghai(Grant No.22ZR1463900)State Key Laboratory of Mechanical System and Vibration(Grant No.MSV202318)the Fundamental Research Funds for the Central Universities(Grant No.22120220649).
文摘Additive manufacturing(AM),particularly fused deposition modeling(FDM),has emerged as a transformative technology in modern manufacturing processes.The dimensional accuracy of FDM-printed parts is crucial for ensuring their functional integrity and performance.To achieve sustainable manufacturing in FDM,it is necessary to optimize the print quality and time efficiency concurrently.However,owing to the complex interactions of printing parameters,achieving a balanced optimization of both remains challenging.This study examines four key factors affecting dimensional accuracy and print time:printing speed,layer thickness,nozzle temperature,and bed temperature.Fifty parameter sets were generated using enhanced Latin hypercube sampling.A whale optimization algorithm(WOA)-enhanced support vector regression(SVR)model was developed to predict dimen-sional errors and print time effectively,with non-dominated sorting genetic algorithm Ⅲ(NSGA-Ⅲ)utilized for multi-objective optimization.The technique for Order Preference by Similarity to Ideal Solution(TOPSIS)was applied to select a balanced solution from the Pareto front.In experimental validation,the parts printed using the optimized parameters exhibited excellent dimensional accuracy and printing efficiency.This study comprehensively considered optimizing the printing time and size to meet quality requirements while achieving higher printing efficiency and aiding in the realization of sustainable manufacturing in the field of AM.In addition,the printing of a specific prosthetic component was used as a case study,highlighting the high demands on both dimensional precision and printing efficiency.The optimized process parameters required significantly less printing time,while satisfying the dimensional accuracy requirements.This study provides valuable insights for achieving sustainable AM using FDM.
基金Under the auspices of the National Natural Science Foundation of China(No.42571228,42401212)National Natural Science Foundation of Shandong(No.ZR2024MD022)。
文摘Green innovation is an important driving force for high-quality development and an important guarantee for the revitalization of the old industrial base in Northeast China.However,research on green innovation is still insufficient.Using the super-efficiency epsilon-based measure Malmquist model,kernel density estimation,and spatial econometric model,this study investigated the spatiotemporal evolution characteristics and influencing factors of green innovation efficiency(GIE)in Northeast China from 2005 to 2020.The results reveal that:1)The GIE in Northeast China has obvious phased characteristics,where 2005-2011 was a period of fluctuating decline while 2012-2020 was a period of fluctuating increase,reflecting the severe resource and environmental constraints faced by the green innovation process.2)The GIE in the Northeast China has a significant spatial dependence,which has not formed a relatively stable spatial club feature.The process for improving the GIE in the Northeast China in the future is still arduous and far off.3)The interweaving and mutual influence of nonequilibrium factors have led to the diversity and complexity of the spatiotemporal pattern evolution of GIE.Overall,the level of economic development and industrial structure has a positive effect,while foreign investment and industrial agglomeration have a negative effect.The direct effects of government regulation,resource endowment,science and technology,environmental regulation,and urbanization are not significant.The research conclusion of this article can provide important reference for the revitalization of Northeast China.
文摘This research investigates the influence of indoor and outdoor factors on photovoltaic(PV)power generation at Utrecht University to accurately predict PV system performance by identifying critical impact factors and improving renewable energy efficiency.To predict plant efficiency,nineteen variables are analyzed,consisting of nine indoor photovoltaic panel characteristics(Open Circuit Voltage(Voc),Short Circuit Current(Isc),Maximum Power(Pmpp),Maximum Voltage(Umpp),Maximum Current(Impp),Filling Factor(FF),Parallel Resistance(Rp),Series Resistance(Rs),Module Temperature)and ten environmental factors(Air Temperature,Air Humidity,Dew Point,Air Pressure,Irradiation,Irradiation Propagation,Wind Speed,Wind Speed Propagation,Wind Direction,Wind Direction Propagation).This study provides a new perspective not previously addressed in the literature.In this study,different machine learning methods such as Multilayer Perceptron(MLP),Multivariate Adaptive Regression Spline(MARS),Multiple Linear Regression(MLR),and Random Forest(RF)models are used to predict power values using data from installed PVpanels.Panel values obtained under real field conditions were used to train the models,and the results were compared.The Multilayer Perceptron(MLP)model was achieved with the highest classification accuracy of 0.990%.The machine learning models used for solar energy forecasting show high performance and produce results close to actual values.Models like Multi-Layer Perceptron(MLP)and Random Forest(RF)can be used in diverse locations based on load demand.
基金Under the auspices of the National Key Research and Development Program of China(No.2019YFA0606603)。
文摘Gross primary production(GPP)is a crucial indicator representing the absorption of atmospheric CO_(2) by vegetation.At present,the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical para-meter leaf area index(LAI),which are not completely synchronized in seasonality with GPP.In this study,we proposed chlorophyll content-based light use efficiency model(CC-LUE)to improve GPP estimates,as chlorophyll is the direct site of photosynthesis,and only the light absorbed by chlorophyll is used in the photosynthetic process.The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content(Chlcanopy)and FPAR.This method was calibrated and validated utiliz-ing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five dif-ferent climate zones.Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions.The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season,outperforming the three widely used LUE models(MODIS-GPP algorithm,Vegetation Photosynthesis Model(VPM),and the eddy covariance-light use efficiency model(EC-LUE)).Additionally,the CC-LUE model(RMSE=0.50 g C/(m^(2)·d))significantly improved the underestimation of GPP during the growing season in semi-arid region,re-markably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%,73.4%,and 37.5%,compared with MOD17(RMSE=2.03 g C/(m^(2)·d)),VPM(RMSE=1.88 g C/(m^(2)·d)),and EC-LUE(RMSE=0.80 g C/(m^(2)·d))model.The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems,thereby provid-ing the possibility of a more precise depiction of forest seasonal carbon uptake.
基金the Special Topic of Key Science and Technology of Fujian Province Fund (No.2006HZ0002-2)
文摘The efficiency of particle screening was studied over a range of vibrational parameters including amplitude, frequency and vibrational direction. The Discrete Element Method (DEM) was used to simulate the screening process. A functional relationship between efficiency and the parameters, both singly and combined, is established. The function is a complicated exponential. Optimal amplitude and frequency values are smaller for particles near the mesh and larger for other particles. The optimum vibration angle is 45° for nearly all kinds of particles. A transverse velocity, V⊥, was defined and V⊥=0.2 m/s was identified to be the most efficient operating point by both simulation and experimental observation. Comparison of these results with those reported by others is included.
文摘Earlier investigators have numerically carried out performance analysis of the invert trap fitted in an open channel using the stochastic discrete phase model(DPM) by assuming the open channel flow to be closed conduit flow under pressure and assuming zero shear stress at the top wall.This is known as the fixed lid model.By assuming the top wall to be a shear free wall,they have been able to show that the velocity distribution looks similar to that of an open channel flow with zero velocity at the bottom and maximum velocity at the top,representing the free water surface,but no information has been provided for the pressure at the free water surface.Because of this assumption,the validation of the model in predicting the trap efficiency has performed significantly poorly.In addition,the free water surface subject to zero gauge pressure cannot be modeled using the fixed lid model because there is no provision of extra space in the form of air space for the fluctuating part of the water surface profile.It can.however,be modeled using the volume of fluid(VOF) model because the VOF model is the appropriate model for open channel or free surface flow.Therefore,in the present study,three-dimensional(3D) computational fluid dynamics(CFD) modeling with the VOF model,which considers open channel flow with a free water surface,along with the stochastic DPM.was used to model the trap efficiency of an invert trap fitted in an open rectangular channel.The governing mathematical flow equations of the VOF model were solved using the ANSYS Fluent 14.0 software,reproducing the experimental conditions exactly.The results show that the 3D CFD predictions using the VOF model closely fit the experimental data for glass bead particles.
文摘Two-oriented agriculture was a complex organism coupling production,economics,society and ecology.Its development process was affected by various factors such as producers,nature,society,etc.In order to overcome measurement error of traditional data envelopment analysis caused by ignoring random,three-stage DEA model was studied to remove environmental factors and random effects.On the foundation of this model was two-oriented agriculture comprehensive production efficiency of 14 cities were estimated in Hunan Province in 2008,and brown forth corresponding policy proposals to promote agricultural development.
基金supported by National Research Foundation of South Africa(UID85783)the National Hub for Energy Efficiency and Demand Side Management and Exxaro
文摘The efficiency of any energy system can be charaterised by the relevant efficiency components in terms of performance, operation, equipment and technology(POET). The overall energy efficiency of the system can be optimised by studying the POET energy efficiency components. For an existing energy system, the improvement of operation efficiency will usually be a quick win for energy efficiency. Therefore, operation efficiency improvement will be the main purpose of this paper. General procedures to establish operation efficiency optimisation models are presented. Model predictive control, a popular technique in modern control theory, is applied to solve the obtained energy models. From the case studies in water pumping systems, model predictive control will have a prosperous application in more energy efficiency problems.
基金supported by the Research Start Funds for Introducing High-level Talents of North China University of Water Resources and Electric Power
文摘This paper expresses the efficient outputs of decisionmaking unit（DMU） as the sum of ＂average outputs＂ forecasted by a GM（1,N） model and ＂increased outputs＂ which reflect the difficulty to realize efficient outputs.The increased outputs are solved by linear programming using data envelopment analysis efficiency theories,wherein a new sample is introduced whose inputs are equal to the budget in the issue No.n ＋ 1 and outputs are forecasted by the GM（1,N） model.The shortcoming in the existing methods that the forecasted efficient outputs may be less than the possible actual outputs according to developing trends of input-output rate in the periods of pre-n is overcome.The new prediction method provides decision-makers with more decisionmaking information,and the initial conditions are easy to be given.
基金supported by the Jiangsu Natural Science Foundation of China(Grant No.BK2012477)the Science Research Foundation of Nanjing Institute of Technology(CKJA201505,JCYJ201618)
文摘Adopting a soft site model built on soft interlayer soil foundation,a shaking table test for soft interlayer soil-isolated structure interaction is conducted to investigate the seismic response of isolated structure on soft site,and analyze its isolation effect.Test results show that the test can reflect the earthquake response characteristics of isolated structure on soft site.It is on soft site that the dynamic characteristics of isolated structure,acceleration magnification factor(AMF)of isolated structure and isolation efficiency of the isolation layer differ from those on rigid foundation with an soil-structure interaction(SSI)effect,represented by the reduction in fundamental vibration frequency of isolated structure and the increase of damping ratio with changes of the SSI effect.SSI can either increase or decrease AMF of isolated structure on soft site,depending on the characteristics of earthquake motion input.Furthermore,the isolation efficiency of isolation layer on soft site is decreased with the SSI effect,which is related to the peak ground acceleration(PGA)and the characteristics of earthquake motion input.
基金Under the auspices of National Natural Science Foundation of China(No.41771131,41301116,41877523)Premium Funding Project for Academic Human Resources Development in Beijing Union University(No.BPHR2017CS13)
文摘Using a heterogeneity stochastic frontier model(HSFM),we empirically investigated the economic efficiency of Beijing-Tianjin-Hebei from 2003 to 2016 and its influencing factors.The key findings of the paper lie in:1)in Beijing-Tianjin-Hebei,the overall economic and technological efficiency tended to increase in a wavelike manner,economic growth slowed down,and there was an obvious imbalance in economic efficiency between the different districts,counties and cities;2)the heterogeneity stochastic frontier production functions(SFPFs)of Beijing,Tianjin and Hebei were different from each other,and investment was still an important impetus of economic growth in Beijing-Tianjin-Hebei;3)economic efficiency was positively correlated with economic agglomeration,human capital,industrial structure,infrastructure,the informatization level,and institutional factors,but negatively correlated with the government role and economic opening.The following policy suggestions are offered:1)to improve regional economic efficiency and reduce the economic gap in Beijing-Tianjin-Hebei,governments must reduce their intervention in economic activities,stimulate the potentials of labor and capital,optimize the structure of human resources,and foster new demographic incentives;2)governments must guide economic factors that are reasonable throughout Beijing-Tianjin-Hebei and strengthen infrastructure construction in underdeveloped regions,thus attaining sustainable economic development;3)governments must plan overall economic growth factors of Beijing-Tianjin-Hebei and promote reasonable economic factors(e.g.,labor,resources,and innovations)across different regions,thus attaining complementary advantages between Beijing,Tianjin,and Hebei.
文摘This research appraises comparative analysis between single diode and double diode model of photovoltaic (PV) solar cells to enhance the conversion efficiency of power engendering PV solar systems. Single diode model is simple and easy to implement, whereas double diode model has better accuracy which acquiesces for more precise forecast of PV systems performance. Exploration is done on the basis of simulation results and MATLAB tool is used to serve this purpose. Simulations are performed by varying distinct model parameters such as solar irradiance, temperature, value of parasitic resistances, ideality factor of diode and number of series and parallel connected solar cells used to assemble PV array. Conspicuous demonstration is executed to analyze effects of these specifications on the efficiency curve and power vs. voltage output characteristics of PV cell for specified models.
基金Supported by Commission of Science Technology and Industry for National Defense(No, C192005C001)
文摘Data envelopment analysis(DEA) model is widely used to evaluate the relative efficiency of producers. It is a kind of objective decision method with multiple indexes. However, the two basic models frequently used at present, the C2R model and the C2GS2 model have limitations when used alone,resulting in evaluations that are often unsatisfactory. In order to solve this problem, a mixed DEA model is built and is used to evaluate the validity of the business efficiency of listed companies. An explanation of how to use this mixed DEA model is offered and its feasibility is verified.
文摘Volumetric efficiency and air charge estimation is one of the most demanding tasks in control of today's internal combustion engines.Specifically,using three-way catalytic converter involves strict control of the air/fuel ratio around the stoichiometric point and hence requires an accurate model for air charge estimation.However,high degrees of complexity and nonlinearity of the gas flow in the internal combustion engine make air charge estimation a challenging task.This is more obvious in engines with variable valve timing systems in which gas flow is more complex and depends on more functional variables.This results in models that are either quite empirical(such as look-up tables),not having interpretability and extrapolation capability,or physically based models which are not appropriate for onboard applications.Solving these problems,a novel semi-empirical model was proposed in this work which only needed engine speed,load,and valves timings for volumetric efficiency prediction.The accuracy and generalizability of the model is shown by its test on numerical and experimental data from three distinct engines.Normalized test errors are 0.0316,0.0152 and 0.24 for the three engines,respectively.Also the performance and complexity of the model were compared with neural networks as typical black box models.While the complexity of the model is less than half of the complexity of neural networks,and its computational cost is approximately 0.12 of that of neural networks and its prediction capability in the considered case studies is usually more.These results show the superiority of the proposed model over conventional black box models such as neural networks in terms of accuracy,generalizability and computational cost.
基金This work was supported by the Global Energy Interconnection Group Limited Science&Technology Project(Project No.:SGGEIG00JYJS1900046).
文摘The front-row shading reduction coefficient is a key parameter used to calculate the system efficiency of a photovoltaic(PV)power station.Based on the Hay anisotropic sky scattering model,the variation rule of solar radiation intensity on the surface of the PV array during the shaded period is simulated,combined with the voltage-current characteristics of the PV modules,and the shadow occlusion operating mode of the PV array is modeled.A method for calculating the loss coefficient of front shadow occlusion based on the division of the PV cell string unit and Hay anisotropic sky scattering model is proposed.This algorithm can accurately evaluate the degree of influence of the PV array layout,wiring mode,array spacing,PV module specifications,and solar radiation on PV power station system efficiency.It provides a basis for optimizing the PV array layout,reducing system loss,and improving PV system efficiency.
基金supported by the National Natural Science Foundation of China under Grant 71804089the Humanities and Social Sciences Youth Foundation of Ministry of Education of China under Grants 18YJCZH034 and 19YJC790128+3 种基金the Jiangsu Postdoctoral Research Foundation underGrant 2018K195C,the Natural Science Foundation of Shandong Province in China under Grant ZR2020QG054the Graduate Education Quality Improvement Project of Shandong Province,China under Grants SDYKC19180 and SDYAL19180The project number of“The quality course in Financial Statistics”is SDYKC19180The project number of“Financial Literacy Oriented Case Library of Derivative Financial Instruments Teaching”is SDYAL19180.
文摘Bohai Rim region is an important economic development area and a large carbon emission area in China.It is of great significance to explore the total factor energy efficiency and its influencing factors for the low carbon transformation and high-quality development of the Bohai Rim region.Based on the total factor energy efficiency framework,the DDF-DEA model was used to calculate the total factor energy efficiency,and the internal and external differences of the total factor energy efficiency were further analyzed.The internal and external influencing factors were determined by ML index method and classical endogenous growth theory,and then the Tobit panel model was used to empirically analyze the action mechanism of all influencing factors of total factor energy efficiency in the Bohai Rim region.The results show that the pure technical efficiency,scale efficiency and technological progress among the internal influencing factors contribute to the improvement of energy efficiency in the Bohai Rim region.Industrial structure,industrial internal structure and ownership structure inhibit the improvement of energy efficiency.Energy consumption structure and energy endowment also have a negative impact on energy efficiency.Therefore,measures such as promoting technological progress,adjusting economic structure and optimizing energy structure will effectively improve total factor energy efficiency in the Bohai Rim region.
文摘Because of ground clutter wave interf e rence,it is difficult to measure smoke screen disturbance in the field.In this pape r,a kind of indoor measurement method of smoke screen disturbance efficiency ba sed on Gaussian diffusion model is put forward.As a characteristic,the measur ement result of smoke screen area density proves that the indoor measurement met hod of smoke screen disturbance efficiency based on Gaussian diffusion model is fea sible.
文摘Applying the slacks-based measure （SBM）-Tobit two-stage model, this paper analyzes energy efficiency in eastern China. First, the SBM model featured in taking non- desired output in calculation was employed to evaluate the energy efficiency in eastern China from 1995 to 2010. The results show that Tianjin, Shanghai and Guangdong have the highest energy efficiency while Hebei has the lowest. Next, we used the panel Tobit model to perform a regression on factors affecting energy efficiency. Our results show that optimizing industrial structure, improving energy structure and enhancing the level of economic reform can contribute to improving energy efficiency. Government influence and technological progress, on the other hand, affect energy efficiency insignificantly. The influence of socio-economic development on the energy efficiency goes from negative to positive, which adheres to the Kuznets curve hypothesis. Our findings are that the socio-economic development in eastern China has not yet passed the ＂turning point of the Kuznets curve ＂.
