The level of ground shaking,as determined by the peak ground acceleration(PGA),can be used to analyze seismic hazard at a certain location and is crucial for constructing earthquake-resistant structures.Predicting the...The level of ground shaking,as determined by the peak ground acceleration(PGA),can be used to analyze seismic hazard at a certain location and is crucial for constructing earthquake-resistant structures.Predicting the PGA immediately after an earthquake occurs allows for the issuing of a warning by an earthquake early warning system.In this study,we propose a deep learning model,ConvMixer,to predict the PGA recorded by weak-motion velocity seismometers in Japan.We use 5-s threecomponent seismograms,from 2 s before until 3 s after the P-wave arrival time of the earthquake.Our dataset comprised more than 50,000 single-station waveforms recorded by 10 seismic stations in the K-NET,Kiki-NET,and Hi-Net networks between 2004 and 2023.The proposed ConvMixer is a patch-based model that extracts global features from input seismic data and predicts the PGA of an earthquake by combining depth and pointwise convolutions.The proposed ConvMixer network had a mean absolute error of 2.143 when applied to the test set and outperformed benchmark deep learning models.In addition,the proposed ConvMixer demonstrated the ability to predict the PGA at the corresponding station site based on 1-second waveforms obtained immediately after the arrival time of the P-wave.展开更多
Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon...Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.展开更多
Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal powe...Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal power generators and BESS(battery energy storage system)taking wind energy emission grading punishment and deep peak clipping into consideration.Firstly,in order to minimize wind abandonment,a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced,and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.Secondly,considering BESS and thermal power,the management approach of BESS-assisted virtual peak clipping of thermal power generators is aimed at reducing the degree of deep peak clipping of thermal power generators and optimizing the output of thermal power generators and the charging and discharging power of BESS.Finally,Give an example of how this strategy has been effective in reducing abandonment rates by 0.66% and 7.46% individually for different wind penetration programs,and the daily average can reduce the peak clipping power output of thermal power generators by 42.97 and 72.31 MWh and enhances the effect and economy of system peak clipping.展开更多
The accurate prediction of peak overpressure of explosion shockwaves is significant in fields such as explosion hazard assessment and structural protection, where explosion shockwaves serve as typical destructive elem...The accurate prediction of peak overpressure of explosion shockwaves is significant in fields such as explosion hazard assessment and structural protection, where explosion shockwaves serve as typical destructive elements. Aiming at the problem of insufficient accuracy of the existing physical models for predicting the peak overpressure of ground reflected waves, two physics-informed machine learning models are constructed. The results demonstrate that the machine learning models, which incorporate physical information by predicting the deviation between the physical model and actual values and adding a physical loss term in the loss function, can accurately predict both the training and out-oftraining dataset. Compared to existing physical models, the average relative error in the predicted training domain is reduced from 17.459%-48.588% to 2%, and the proportion of average relative error less than 20% increased from 0% to 59.4% to more than 99%. In addition, the relative average error outside the prediction training set range is reduced from 14.496%-29.389% to 5%, and the proportion of relative average error less than 20% increased from 0% to 71.39% to more than 99%. The inclusion of a physical loss term enforcing monotonicity in the loss function effectively improves the extrapolation performance of machine learning. The findings of this study provide valuable reference for explosion hazard assessment and anti-explosion structural design in various fields.展开更多
Wave information retrieval from videos captured by a single camera has been increasingly applied in marine observation.However,when the camera observes ocean waves at low grazing angles,the accurate extraction of wave...Wave information retrieval from videos captured by a single camera has been increasingly applied in marine observation.However,when the camera observes ocean waves at low grazing angles,the accurate extraction of wave information from videos will be affected by the interference of the fine ripples on the sea surface.To solve this problem,this study develops a method for estimating peak wave periods from videos captured at low grazing angles.The method extracts the motion of the sea surface texture from the video and obtains the peak wave period via the spectral analysis.The calculation results captured from real-world videos are compared with those obtained from X-band radar inversion and tracking buoy movement,with maximum deviations of 8%and 14%,respectively.The analysis of the results shows that the peak wave period of the method has good stability.In addition,this paper uses a pinhole camera model to convert the displacement of the texture from pixel height to actual height and performs moving average filtering on the displacement of the texture,thus conducting a preliminary exploration of the inversion of significant wave height.This study helps to extend the application of sea surface videos.展开更多
According to the multi-time-scale characteristics of power generation and demand-side response(DR)resources,as well as the improvement of prediction accuracy along with the approaching operating point,a rolling peak s...According to the multi-time-scale characteristics of power generation and demand-side response(DR)resources,as well as the improvement of prediction accuracy along with the approaching operating point,a rolling peak shaving optimization model consisting of three different time scales has been proposed.The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination,generation power,and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response characteristics of the concentrating solar power(CSP).At the same time,in order to improve the accuracy of the scheduling results,the combination of the day-ahead peak shaving phase with scenario-based stochastic programming can further reduce the influence of wind power prediction errors on scheduling results.The testing results have shown that by optimizing the allocation of scheduling resources in each phase,it can effectively reduce the number of starts and stops of thermal power units and improve the economic efficiency of system operation.The spinning reserve capacity is reduced,and the effectiveness of the peak shaving strategy is verified.展开更多
This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the...This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the MCNPX code for analysing neutron behavior and the PARET/ANL code for understanding power variations, to get a clearer picture of the reactor’s performance. The analysis covers the initial six years of GHARR-1’s operation and includes projections for its whole 60-year lifespan. We closely observed the patterns of both the highest and average PPFs at 21 axial nodes, with measurements taken every ten years. The findings of this study reveal important patterns in power distribution within the core, which are essential for improving the safety regulations and fuel management techniques of the reactor. We provide a meticulous approach, extensive data, and an analysis of the findings, highlighting the significance of continuous monitoring and analysis for proactive management of nuclear reactors. The findings of this study not only enhance our comprehension of nuclear reactor safety but also carry significant ramifications for sustainable energy progress in Ghana and the wider global context. Nuclear engineering is essential in tackling global concerns, such as the demand for clean and dependable energy sources. Research on optimising nuclear reactors, particularly in terms of safety and efficiency, is crucial for the ongoing advancement and acceptance of nuclear energy.展开更多
Smoothed cepstral peak prominence(CPPs)is a measurement of the distance from the prominent cepstral peak to the linear regression line directly beneath it.Variations of CPPs data acquisition and analysis lead to the c...Smoothed cepstral peak prominence(CPPs)is a measurement of the distance from the prominent cepstral peak to the linear regression line directly beneath it.Variations of CPPs data acquisition and analysis lead to the complexity of the clinical cut-off values,and there are no agreeable values for a specific voice disorder,such as hypokinetic dysarthria associated with Parkinson’s disease(PD).This study examined the CPPs in people with hypokinetic dysarthria associated with PD compared with healthy participants.Results demonstrated significant differences in speech tasks of sustained vowel and connected speech,with CPPs of connected speech more sensitive to dysphonia and gender difference in PD participants.Males in PD participants presented higher CPPs for sustained vowels and lower CPPs for connected speech than females.It is implied that a consistent clinical application protocol is necessary,and multiple acoustic measures are needed to ensure the accuracy of clinical decisions.展开更多
This study utilizes empirical equations to describe the propagation of vibrations induced by blasting, with the goal of predicting the attenuation of Peak Particle Velocity (PPV) at the Yaramoko mine in Bagassi, Burki...This study utilizes empirical equations to describe the propagation of vibrations induced by blasting, with the goal of predicting the attenuation of Peak Particle Velocity (PPV) at the Yaramoko mine in Bagassi, Burkina Faso, a site characterized by granitoid rock. Four empirical PPV prediction equations were employed, so-called Duvall & Fogelson (or the United States Bureau of Mines “USBM”), Langefors and Kihlstrom, Ambressys-Hendron, and the Bureau of Indian Standard. The constant parameters for each of these equations, referred to as site constants, were derived from linear regression curves. The results show that the site constants k, a, and b of 4762, 0.869, and 1.737, respectively, derived from the general prediction equation by Davies, PPV = kQaD−b, based on Duvall & Fogelson, are in good agreement with values of 4690, 0.9, and 1.69, respectively, for similar rock types in Spain. Regarding the impacts of blasting on houses, the findings indicate that houses built from laterite-block bricks in the village of Bagassi are the most vulnerable to vibration waves, followed by those constructed with cinder-block bricks. In contrast, houses made of banco bricks are the most resilient. Additionally, it was determined that during blasting operations, adjusting the blasting parameters to ensure the PPV does not exceed 2 mm/s at the level of nearby dwellings can minimize the appearance of cracks in houses.展开更多
Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,i...Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,is an important ecological barrier area in the temperate arid zone.The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve.In the present study,we assessed the spatiotemporal variations of four ecosystem services(including net primary productivity(NPP),water yield,soil conservation,and habitat quality)in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.In addition,the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis,and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector.During the study period,NPP and soil conservation values in the reserve increased by 48.20%and 25.56%,respectively;conversely,water yield decreased by 16.56%,and there was no significant change in habitat quality.Spatially,both NPP and habitat quality values were higher in the northern part and lower in the southern part,whereas water yield showed an opposite trend.Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation,and exhibited a trade-off relationship with water yield.Water yield and habitat quality also had a trade-off relationship.NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index(NDVI),respectively,while water yield and soil conservation were more affected by digital elevation model(DEM).Therefore,attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management.The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.展开更多
基金the National Research Institute of Astronomy and Geophysics (NRIAG) for supporting this work
文摘The level of ground shaking,as determined by the peak ground acceleration(PGA),can be used to analyze seismic hazard at a certain location and is crucial for constructing earthquake-resistant structures.Predicting the PGA immediately after an earthquake occurs allows for the issuing of a warning by an earthquake early warning system.In this study,we propose a deep learning model,ConvMixer,to predict the PGA recorded by weak-motion velocity seismometers in Japan.We use 5-s threecomponent seismograms,from 2 s before until 3 s after the P-wave arrival time of the earthquake.Our dataset comprised more than 50,000 single-station waveforms recorded by 10 seismic stations in the K-NET,Kiki-NET,and Hi-Net networks between 2004 and 2023.The proposed ConvMixer is a patch-based model that extracts global features from input seismic data and predicts the PGA of an earthquake by combining depth and pointwise convolutions.The proposed ConvMixer network had a mean absolute error of 2.143 when applied to the test set and outperformed benchmark deep learning models.In addition,the proposed ConvMixer demonstrated the ability to predict the PGA at the corresponding station site based on 1-second waveforms obtained immediately after the arrival time of the P-wave.
文摘Based on the supply-side perspective,the improved STIRPAT model is applied to reveal the mechanisms of supply-side factors such as human,capital,technology,industrial synergy,institutions and economic growth on carbon emissions in the Yangtze River Delta(YRD)through path analysis,and to forecast carbon emissions in the YRD from the baseline scenario,factor regulation scenario and integrated scenario to reach the peak.The results show that:(1)Jiangsu's high carbon emission pattern is the main reason for the YRD hindering the synergistic regulation of carbon emissions.(2)Human factors,institutional factors and economic growth factors can all contribute to carbon emissions in the YRD region,while technological and industrial factors can generally suppress carbon emissions in the YRD region.(3)Under the capital regulation scenario,the YRD region has the highest level of carbon emission synergy,with Jiangsu reaching its peak five years earlier.Under the balanced regulation scenario,the YRD region as a whole,Jiangsu,Zhejiang and Anhui reach the peak as scheduled.
基金supported by Jilin Province Higher Education Teaching Reform Research Project in 2021(JLJY202186163419).
文摘Peak load and wind energy emission pressure rise more as wind energy penetration keeps growing,which affects the stabilization of the PS(power system).This paper suggests integrated optimal dispatching of thermal power generators and BESS(battery energy storage system)taking wind energy emission grading punishment and deep peak clipping into consideration.Firstly,in order to minimize wind abandonment,a hierarchical wind abandonment penalty strategy based on fuzzy control is designed and introduced,and the optimal grid-connected power of wind energy is determined as a result of minimizing the peak cutting cost of the system.Secondly,considering BESS and thermal power,the management approach of BESS-assisted virtual peak clipping of thermal power generators is aimed at reducing the degree of deep peak clipping of thermal power generators and optimizing the output of thermal power generators and the charging and discharging power of BESS.Finally,Give an example of how this strategy has been effective in reducing abandonment rates by 0.66% and 7.46% individually for different wind penetration programs,and the daily average can reduce the peak clipping power output of thermal power generators by 42.97 and 72.31 MWh and enhances the effect and economy of system peak clipping.
文摘The accurate prediction of peak overpressure of explosion shockwaves is significant in fields such as explosion hazard assessment and structural protection, where explosion shockwaves serve as typical destructive elements. Aiming at the problem of insufficient accuracy of the existing physical models for predicting the peak overpressure of ground reflected waves, two physics-informed machine learning models are constructed. The results demonstrate that the machine learning models, which incorporate physical information by predicting the deviation between the physical model and actual values and adding a physical loss term in the loss function, can accurately predict both the training and out-oftraining dataset. Compared to existing physical models, the average relative error in the predicted training domain is reduced from 17.459%-48.588% to 2%, and the proportion of average relative error less than 20% increased from 0% to 59.4% to more than 99%. In addition, the relative average error outside the prediction training set range is reduced from 14.496%-29.389% to 5%, and the proportion of relative average error less than 20% increased from 0% to 71.39% to more than 99%. The inclusion of a physical loss term enforcing monotonicity in the loss function effectively improves the extrapolation performance of machine learning. The findings of this study provide valuable reference for explosion hazard assessment and anti-explosion structural design in various fields.
基金The Key R&D Program of Shandong Province under contract No.2023CXPT101.
文摘Wave information retrieval from videos captured by a single camera has been increasingly applied in marine observation.However,when the camera observes ocean waves at low grazing angles,the accurate extraction of wave information from videos will be affected by the interference of the fine ripples on the sea surface.To solve this problem,this study develops a method for estimating peak wave periods from videos captured at low grazing angles.The method extracts the motion of the sea surface texture from the video and obtains the peak wave period via the spectral analysis.The calculation results captured from real-world videos are compared with those obtained from X-band radar inversion and tracking buoy movement,with maximum deviations of 8%and 14%,respectively.The analysis of the results shows that the peak wave period of the method has good stability.In addition,this paper uses a pinhole camera model to convert the displacement of the texture from pixel height to actual height and performs moving average filtering on the displacement of the texture,thus conducting a preliminary exploration of the inversion of significant wave height.This study helps to extend the application of sea surface videos.
基金support of the projects Youth Science Foundation of Gansu Province(Source-Grid-Load Multi-Time Interval Optimization Scheduling Method Considering Wind-PV-CSP Combined DC Transmission,No.22JR11RA148)Youth Science Foundation of Lanzhou Jiaotong University(Research on Coordinated Dispatching Control Strategy of High Proportion New Energy Transmission Power System with CSP Power Generation,No.2020011).
文摘According to the multi-time-scale characteristics of power generation and demand-side response(DR)resources,as well as the improvement of prediction accuracy along with the approaching operating point,a rolling peak shaving optimization model consisting of three different time scales has been proposed.The proposed peak shaving optimization model considers not only the generation resources of two different response speeds but also the two different DR resources and determines each unit combination,generation power,and demand response strategy on different time scales so as to participate in the peaking of the power system by taking full advantage of the fast response characteristics of the concentrating solar power(CSP).At the same time,in order to improve the accuracy of the scheduling results,the combination of the day-ahead peak shaving phase with scenario-based stochastic programming can further reduce the influence of wind power prediction errors on scheduling results.The testing results have shown that by optimizing the allocation of scheduling resources in each phase,it can effectively reduce the number of starts and stops of thermal power units and improve the economic efficiency of system operation.The spinning reserve capacity is reduced,and the effectiveness of the peak shaving strategy is verified.
文摘This study aims to thoroughly investigate the axial power peaking factors (PPF) within the low-enriched uranium (LEU) core of the Ghana Research Reactor-1 (GHARR-1). This study uses advanced simulation tools, like the MCNPX code for analysing neutron behavior and the PARET/ANL code for understanding power variations, to get a clearer picture of the reactor’s performance. The analysis covers the initial six years of GHARR-1’s operation and includes projections for its whole 60-year lifespan. We closely observed the patterns of both the highest and average PPFs at 21 axial nodes, with measurements taken every ten years. The findings of this study reveal important patterns in power distribution within the core, which are essential for improving the safety regulations and fuel management techniques of the reactor. We provide a meticulous approach, extensive data, and an analysis of the findings, highlighting the significance of continuous monitoring and analysis for proactive management of nuclear reactors. The findings of this study not only enhance our comprehension of nuclear reactor safety but also carry significant ramifications for sustainable energy progress in Ghana and the wider global context. Nuclear engineering is essential in tackling global concerns, such as the demand for clean and dependable energy sources. Research on optimising nuclear reactors, particularly in terms of safety and efficiency, is crucial for the ongoing advancement and acceptance of nuclear energy.
文摘Smoothed cepstral peak prominence(CPPs)is a measurement of the distance from the prominent cepstral peak to the linear regression line directly beneath it.Variations of CPPs data acquisition and analysis lead to the complexity of the clinical cut-off values,and there are no agreeable values for a specific voice disorder,such as hypokinetic dysarthria associated with Parkinson’s disease(PD).This study examined the CPPs in people with hypokinetic dysarthria associated with PD compared with healthy participants.Results demonstrated significant differences in speech tasks of sustained vowel and connected speech,with CPPs of connected speech more sensitive to dysphonia and gender difference in PD participants.Males in PD participants presented higher CPPs for sustained vowels and lower CPPs for connected speech than females.It is implied that a consistent clinical application protocol is necessary,and multiple acoustic measures are needed to ensure the accuracy of clinical decisions.
文摘This study utilizes empirical equations to describe the propagation of vibrations induced by blasting, with the goal of predicting the attenuation of Peak Particle Velocity (PPV) at the Yaramoko mine in Bagassi, Burkina Faso, a site characterized by granitoid rock. Four empirical PPV prediction equations were employed, so-called Duvall & Fogelson (or the United States Bureau of Mines “USBM”), Langefors and Kihlstrom, Ambressys-Hendron, and the Bureau of Indian Standard. The constant parameters for each of these equations, referred to as site constants, were derived from linear regression curves. The results show that the site constants k, a, and b of 4762, 0.869, and 1.737, respectively, derived from the general prediction equation by Davies, PPV = kQaD−b, based on Duvall & Fogelson, are in good agreement with values of 4690, 0.9, and 1.69, respectively, for similar rock types in Spain. Regarding the impacts of blasting on houses, the findings indicate that houses built from laterite-block bricks in the village of Bagassi are the most vulnerable to vibration waves, followed by those constructed with cinder-block bricks. In contrast, houses made of banco bricks are the most resilient. Additionally, it was determined that during blasting operations, adjusting the blasting parameters to ensure the PPV does not exceed 2 mm/s at the level of nearby dwellings can minimize the appearance of cracks in houses.
基金This research was funded by the Key Laboratory for Sustainable Development of Xinjiang's Historical and Cultural Tourism,Xinjiang University,China(LY2022-06)the Tianchi Talent Project.
文摘Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation.The Tianchi Bogda Peak Natural Reserve(TBPNR),located in Xinjiang Uygur Autonomous Region,China,is an important ecological barrier area in the temperate arid zone.The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve.In the present study,we assessed the spatiotemporal variations of four ecosystem services(including net primary productivity(NPP),water yield,soil conservation,and habitat quality)in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs(InVEST)model.In addition,the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis,and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector.During the study period,NPP and soil conservation values in the reserve increased by 48.20%and 25.56%,respectively;conversely,water yield decreased by 16.56%,and there was no significant change in habitat quality.Spatially,both NPP and habitat quality values were higher in the northern part and lower in the southern part,whereas water yield showed an opposite trend.Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation,and exhibited a trade-off relationship with water yield.Water yield and habitat quality also had a trade-off relationship.NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index(NDVI),respectively,while water yield and soil conservation were more affected by digital elevation model(DEM).Therefore,attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management.The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.
