Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a p...Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a parameter estimation model of the boost phase based on trajectory plane parametric cutting.The use of the plane passing through the geo-center and the cutting sequence line of sight(LOS)generates the trajectory-cutting plane.With the coefficient of the trajectory cutting plane directly used as the parameter to be estimated,a motion parameter estimation model in space non-cooperative targets is established,and the Gauss-Newton iteration method is used to solve the flight parameters.The experimental results show that the estimation algorithm proposed in this paper weakly relies on prior information and has higher estimation accuracy,providing a practical new idea and method for the parameter estimation of space non-cooperative targets under single-satellite warning.展开更多
Modeling of unsteady aerodynamic loads at high angles of attack using a small amount of experimental or simulation data to construct predictive models for unknown states can greatly improve the efficiency of aircraft ...Modeling of unsteady aerodynamic loads at high angles of attack using a small amount of experimental or simulation data to construct predictive models for unknown states can greatly improve the efficiency of aircraft unsteady aerodynamic design and flight dynamics analysis.In this paper,aiming at the problems of poor generalization of traditional aerodynamic models and intelligent models,an intelligent aerodynamic modeling method based on gated neural units is proposed.The time memory characteristics of the gated neural unit is fully utilized,thus the nonlinear flow field characterization ability of the learning and training process is enhanced,and the generalization ability of the whole prediction model is improved.The prediction and verification of the model are carried out under the maneuvering flight condition of NACA0015 airfoil.The results show that the model has good adaptability.In the interpolation prediction,the maximum prediction error of the lift and drag coefficients and the moment coefficient does not exceed 10%,which can basically represent the variation characteristics of the entire flow field.In the construction of extrapolation models,the training model based on the strong nonlinear data has good accuracy for weak nonlinear prediction.Furthermore,the error is larger,even exceeding 20%,which indicates that the extrapolation and generalization capabilities need to be further optimized by integrating physical models.Compared with the conventional state space equation model,the proposed method can improve the extrapolation accuracy and efficiency by 78%and 60%,respectively,which demonstrates the applied potential of this method in aerodynamic modeling.展开更多
Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the thr...Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the three-dimensional(3D)surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging.The system captures synchronized images of particles in free fall,employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices.A pre-trained segmentation model is utilized to eliminate the background of the images.The Shape from Silhouettes(SfS)algorithm is then applied to generate 3D voxel data,followed by the Marching Cubes algorithm to construct the 3D surface contour.Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy,with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.展开更多
The complete description of outdoor luminous and thermal environment is the basis for daylight utilization design with simulation tools.Nevertheless,Typical Meteorological Year(TMY)and generation method specifically d...The complete description of outdoor luminous and thermal environment is the basis for daylight utilization design with simulation tools.Nevertheless,Typical Meteorological Year(TMY)and generation method specifically developed for the energy simulation of daylight-utilized buildings is still unavailable currently.Luminous environment parameters have not been taken into consideration in existing TMY generation methods.In this study,the feasibility of existing TMY generation process has been examined.A generic office model implementing sided window daylighting is established.Historical meteorological data of Hong Kong region from 1979 to 2007 have been collected and three existing weighting schemes are applied during the Typical Meteorological Month(TMM)selection procedures.Three TMY files for Hong Kong are generated and used to conduct integrated Climate-Based Daylight Modeling and building energy simulation.The result demonstrates that,on annual basis,the energy consumption results obtained from the generated TMY files are in good agreements with the long-term mean annual value.The maximum deviation of annual energy consumptions for the generated TMY files is only 1.8%.However,further analysis on monthly basis shows that all the three generated TMY files fail to fully represent the long-term monthly mean level.The maximum deviation of monthly energy consumptions for the generated TMY files can reach up to 11%.As the energy performance daylight utilization is subject to weather change,analysis on daily and monthly energy level is important,especially during design stage.The deficiency of existing TMM selection process and TMY generation method indicates the necessity to develop a corresponding typical weather data input with finer resolution for the energy simulation of daylight-related buildings.展开更多
More than half of the annual global concrete materials were produced in China due to the rapid developing construction industry,which partly led to the shortage of river sand.However,mining rate exceeds the natural re...More than half of the annual global concrete materials were produced in China due to the rapid developing construction industry,which partly led to the shortage of river sand.However,mining rate exceeds the natural replenishment rate of river sand recently,resulting in depletion of natural river sand accumulation.The increasing demand of river sand influences lots of aspects including altered landforms,increasing carbon emissions,ecological deterioration,international trades and disputes.To face the river sand resource shortage in China and to propose possible coping strategies,the data of river sand for construction in China and other related data were collected,and it is suggested that effective policy measures should be taken right now to protect river sand and strictly manage sand mining.Professional solutions for river sand shortage can be summarized as“5Rs”principle,which includes reduce,recycle.reuse,replace and recover.System dynamic model is established to predict the trend of river sand shortage and it was predicted that the gap between river sand supply and demand will come up to 63%.The impact of three policy scenarios is tested in the model,and the gap can be reduced to 35%by single policy scenario,while the scenario with all policy measures is able to reduce the contradiction between supply and demand to 4%.Suggestions are proposed from the aspects of structural and material technology,policy measures and international alliances.Attention should be paid to the shortage of river resources,to realize the sustainable development of the construction industry and other related industries,and to promote the harmonious coexistence of human and nature.展开更多
The research on the influencing factors of carbon emissions from urban buildings is of great significance for the reduction of carbon in the urban building sector and even the realization of the city’s the carbon pea...The research on the influencing factors of carbon emissions from urban buildings is of great significance for the reduction of carbon in the urban building sector and even the realization of the city’s the carbon peak and neutrality goals.In this paper,combined with the ridge regression method,the STIRPAT model is used to establish a new model for influencing factors of building carbon emissions in Suzhou,and the factors such as urbanization rate,the number of permanent residents,per capita construction and tertiary industry added value,and per capita disposable income are analyzed.The analysis results show that the urbanization rate is the primary driving factor for building carbon emissions in Suzhou,followed by the number of permanent residents,then the added value of the per capita construction industry and tertiary industry,and finally the per capita disposable income.The conclusions of this paper indicate that industrialization and urbanization have strongly promoted the growth of building carbon emissions in Suzhou.In the future,with the continuous development of industrialization and urbanization and the increase of population,Suzhou City can rationally plan urban development boundaries to promote green and low-carbon transformation and development in the field of urban and rural construction,improve residents’low-carbon awareness,and advocate green and low-carbon behavior of residents to reduce building carbon emissions.展开更多
基金supported in part by the National Natural Science Foundation of China(Nos.42271448,41701531)the Key Laboratory of Land Satellite Remote Sensing Application,Ministry of Natural Resources of the People’s Republic of China(No.KLSMNRG202317)。
文摘Under single-satellite observation,the parameter estimation of the boost phase of high-precision space noncooperative targets requires prior information.To improve the accuracy without prior information,we propose a parameter estimation model of the boost phase based on trajectory plane parametric cutting.The use of the plane passing through the geo-center and the cutting sequence line of sight(LOS)generates the trajectory-cutting plane.With the coefficient of the trajectory cutting plane directly used as the parameter to be estimated,a motion parameter estimation model in space non-cooperative targets is established,and the Gauss-Newton iteration method is used to solve the flight parameters.The experimental results show that the estimation algorithm proposed in this paper weakly relies on prior information and has higher estimation accuracy,providing a practical new idea and method for the parameter estimation of space non-cooperative targets under single-satellite warning.
基金supported in part by the National Natural Science Foundation of China (No. 12202363)。
文摘Modeling of unsteady aerodynamic loads at high angles of attack using a small amount of experimental or simulation data to construct predictive models for unknown states can greatly improve the efficiency of aircraft unsteady aerodynamic design and flight dynamics analysis.In this paper,aiming at the problems of poor generalization of traditional aerodynamic models and intelligent models,an intelligent aerodynamic modeling method based on gated neural units is proposed.The time memory characteristics of the gated neural unit is fully utilized,thus the nonlinear flow field characterization ability of the learning and training process is enhanced,and the generalization ability of the whole prediction model is improved.The prediction and verification of the model are carried out under the maneuvering flight condition of NACA0015 airfoil.The results show that the model has good adaptability.In the interpolation prediction,the maximum prediction error of the lift and drag coefficients and the moment coefficient does not exceed 10%,which can basically represent the variation characteristics of the entire flow field.In the construction of extrapolation models,the training model based on the strong nonlinear data has good accuracy for weak nonlinear prediction.Furthermore,the error is larger,even exceeding 20%,which indicates that the extrapolation and generalization capabilities need to be further optimized by integrating physical models.Compared with the conventional state space equation model,the proposed method can improve the extrapolation accuracy and efficiency by 78%and 60%,respectively,which demonstrates the applied potential of this method in aerodynamic modeling.
基金Supported by the Key R&D Projects in Shaanxi Province(2022JBGS3-08)。
文摘Rapidly and accurately assessing the geometric characteristics of coarse aggregate particles is crucial for ensuring pavement performance in highway engineering.This article introduces an innovative system for the three-dimensional(3D)surface reconstruction of coarse aggregate particles using occlusion-free multi-view imaging.The system captures synchronized images of particles in free fall,employing a matte sphere and a nonlinear optimization approach to estimate the camera projection matrices.A pre-trained segmentation model is utilized to eliminate the background of the images.The Shape from Silhouettes(SfS)algorithm is then applied to generate 3D voxel data,followed by the Marching Cubes algorithm to construct the 3D surface contour.Validation against standard parts and diverse coarse aggregate particles confirms the method's high accuracy,with an average measurement precision of 0.434 mm and a significant increase in scanning and reconstruction efficiency.
基金supported in part by grants from Science and Technology Support Carbon Emission Peak and Carbon Neutralization Special Project of Shanghai 2021“Science and Technology Innovation Action Plan”[grant numbers 21DZ1208400].
文摘The complete description of outdoor luminous and thermal environment is the basis for daylight utilization design with simulation tools.Nevertheless,Typical Meteorological Year(TMY)and generation method specifically developed for the energy simulation of daylight-utilized buildings is still unavailable currently.Luminous environment parameters have not been taken into consideration in existing TMY generation methods.In this study,the feasibility of existing TMY generation process has been examined.A generic office model implementing sided window daylighting is established.Historical meteorological data of Hong Kong region from 1979 to 2007 have been collected and three existing weighting schemes are applied during the Typical Meteorological Month(TMM)selection procedures.Three TMY files for Hong Kong are generated and used to conduct integrated Climate-Based Daylight Modeling and building energy simulation.The result demonstrates that,on annual basis,the energy consumption results obtained from the generated TMY files are in good agreements with the long-term mean annual value.The maximum deviation of annual energy consumptions for the generated TMY files is only 1.8%.However,further analysis on monthly basis shows that all the three generated TMY files fail to fully represent the long-term monthly mean level.The maximum deviation of monthly energy consumptions for the generated TMY files can reach up to 11%.As the energy performance daylight utilization is subject to weather change,analysis on daily and monthly energy level is important,especially during design stage.The deficiency of existing TMM selection process and TMY generation method indicates the necessity to develop a corresponding typical weather data input with finer resolution for the energy simulation of daylight-related buildings.
基金the research grants from the National Natural Science Foundation of China(No:51325802)the National Key R&D Program of China(2022YFC3803400).
文摘More than half of the annual global concrete materials were produced in China due to the rapid developing construction industry,which partly led to the shortage of river sand.However,mining rate exceeds the natural replenishment rate of river sand recently,resulting in depletion of natural river sand accumulation.The increasing demand of river sand influences lots of aspects including altered landforms,increasing carbon emissions,ecological deterioration,international trades and disputes.To face the river sand resource shortage in China and to propose possible coping strategies,the data of river sand for construction in China and other related data were collected,and it is suggested that effective policy measures should be taken right now to protect river sand and strictly manage sand mining.Professional solutions for river sand shortage can be summarized as“5Rs”principle,which includes reduce,recycle.reuse,replace and recover.System dynamic model is established to predict the trend of river sand shortage and it was predicted that the gap between river sand supply and demand will come up to 63%.The impact of three policy scenarios is tested in the model,and the gap can be reduced to 35%by single policy scenario,while the scenario with all policy measures is able to reduce the contradiction between supply and demand to 4%.Suggestions are proposed from the aspects of structural and material technology,policy measures and international alliances.Attention should be paid to the shortage of river resources,to realize the sustainable development of the construction industry and other related industries,and to promote the harmonious coexistence of human and nature.
基金supported by he National Natural Science Foundation of China(No.72140003).
文摘The research on the influencing factors of carbon emissions from urban buildings is of great significance for the reduction of carbon in the urban building sector and even the realization of the city’s the carbon peak and neutrality goals.In this paper,combined with the ridge regression method,the STIRPAT model is used to establish a new model for influencing factors of building carbon emissions in Suzhou,and the factors such as urbanization rate,the number of permanent residents,per capita construction and tertiary industry added value,and per capita disposable income are analyzed.The analysis results show that the urbanization rate is the primary driving factor for building carbon emissions in Suzhou,followed by the number of permanent residents,then the added value of the per capita construction industry and tertiary industry,and finally the per capita disposable income.The conclusions of this paper indicate that industrialization and urbanization have strongly promoted the growth of building carbon emissions in Suzhou.In the future,with the continuous development of industrialization and urbanization and the increase of population,Suzhou City can rationally plan urban development boundaries to promote green and low-carbon transformation and development in the field of urban and rural construction,improve residents’low-carbon awareness,and advocate green and low-carbon behavior of residents to reduce building carbon emissions.
