We extend the third perturbation theory to study the polarization control behavior of the intermediate state absorption in Nd^（3＋）ions. The results show that coherent interference can occur between the single-photo...We extend the third perturbation theory to study the polarization control behavior of the intermediate state absorption in Nd^（3＋）ions. The results show that coherent interference can occur between the single-photon and three-photon excitation pathways, and depends on the central frequency of the femtosecond laser field. Moreover,single-photon and three-photon absorptions have different polarization control efficiencies, and the relative weight of three-photon absorption in the whole excitation processes can increase with increasing the laser intensity.Therefore, the enhancement or suppression of the intermediate state absorption can be realized and manipulated by properly designing the intensity and central frequency of the polarization modulated femtosecond laser field.This research can not only enrich theoretical research methods for the up-conversion luminescence manipulation of rare-earth ions, but also can provide a clear physical picture for understanding and controlling multi-photon absorption in a multiple energy level system.展开更多
In order to overcome the low precision and weak applicability problems of the current municipal water network state simulation model, the water network structure is studied. Since the telemetry system has been applied...In order to overcome the low precision and weak applicability problems of the current municipal water network state simulation model, the water network structure is studied. Since the telemetry system has been applied increasingly in the water network, and in order to reflect the network operational condition more accurately, a new water network macroscopic model is developed by taking the auto-control adjusting valve opening state into consideration. Then for highly correlated or collinear independent variables in the model, the partial least squares (PLS) regression method provides a model solution which can distinguish between the system information and the noisy data. Finally, a hypothetical water network is introduced for validating the model. The simulation results show that the relative error is less than 5.2%, indicating that the model is efficient and feasible, and has better generalization performance.展开更多
This paper studies the deterioration of bridge substructures utilizing the Long-Term Bridge Performance(LTBP)Program InfoBridge^(TM)and develops a survival model using Cox proportional hazards regression.The survival ...This paper studies the deterioration of bridge substructures utilizing the Long-Term Bridge Performance(LTBP)Program InfoBridge^(TM)and develops a survival model using Cox proportional hazards regression.The survival analysis is based on the National Bridge Inventory(NBI)dataset.The study calculates the survival rate of reinforced and prestressed concrete piles on bridges under marine conditions over a 29-year span(from 1992 to 2020).The state of Maryland is the primary focus of this study,with data from three neighboring regions,the District of Columbia,Virginia,and Delaware to expand the sample size.The data obtained from the National Bridge Inventory are condensed and filtered to acquire the most relevant information for model development.The Cox proportional hazards regression is applied to the condensed NBI data with six parameters:Age,ADT,ADTT,number of spans,span length,and structural length.Two survival models are generated for the bridge substructures:Reinforced and prestressed concrete piles in Maryland and reinforced and prestressed concrete piles in wet service conditions in the District of Columbia,Maryland,Delaware,and Virginia.Results from the Cox proportional hazards regression are used to construct Markov chains to demonstrate the sequence of the deterioration of bridge substructures.The Markov chains can be used as a tool to assist in the prediction and decision-making for repair,rehabilitation,and replacement of bridge piles.Based on the numerical model,the Pile Assessment Matrix Program(PAM)is developed to facilitate the assessment and maintenance of current bridge structures.The program integrates the NBI database with the inspection and research reports from various states’department of transportation,to serve as a tool for condition state simulation based on maintenance or rehabilitation strategies.展开更多
Wind turbine maintenance optimization faces challenges in balancing economic efficiency with operational reliability under environmental uncertainty.Traditional maintenance approaches exhibit limitations in adaptive d...Wind turbine maintenance optimization faces challenges in balancing economic efficiency with operational reliability under environmental uncertainty.Traditional maintenance approaches exhibit limitations in adaptive decision-making,leading to increased operational costs and reliability risks.This study develops a physicsinformed reinforcement learning framework that integrates established domain knowledge with adaptive deci-sion algorithms.The approach embeds physical principles-including Weibull wind dynamics and multi-stage degradation models-into a reinforcement learning architecture,while introducing bidirectional temperature-degradation coupling for enhanced failure prediction.A high-fidelity simulation environment enables policy training through Proximal Policy Optimization,capturing complex interactions between environmental vari-ability and equipment deterioration.The framework was validated through case study implementation using northern China wind farm operational data.Results demonstrate zero-failure operation over simulated 19-year lifecycles,with economic performance improvements of 109.3%and 54.5%compared to conventional periodic and threshold-based maintenance strategies.By integrating physical constraints with intelligent algorithms,the method achieves adaptive maintenance decisions based on multi-dimensional state information.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 51132004,11474096,11604199,U1704145 and 11747101the Science and Technology Commission of Shanghai Municipality under Grant No 14JC1401500+1 种基金the Henan Provincial Natural Science Foundation of China under Grant No 182102210117the Higher Education Key Program of He’nan Province of China under Grant Nos 17A140025 and 16A140030
文摘We extend the third perturbation theory to study the polarization control behavior of the intermediate state absorption in Nd^（3＋）ions. The results show that coherent interference can occur between the single-photon and three-photon excitation pathways, and depends on the central frequency of the femtosecond laser field. Moreover,single-photon and three-photon absorptions have different polarization control efficiencies, and the relative weight of three-photon absorption in the whole excitation processes can increase with increasing the laser intensity.Therefore, the enhancement or suppression of the intermediate state absorption can be realized and manipulated by properly designing the intensity and central frequency of the polarization modulated femtosecond laser field.This research can not only enrich theoretical research methods for the up-conversion luminescence manipulation of rare-earth ions, but also can provide a clear physical picture for understanding and controlling multi-photon absorption in a multiple energy level system.
基金Supported by Tianjin Natural Science Foundation( No. 003611611).
文摘In order to overcome the low precision and weak applicability problems of the current municipal water network state simulation model, the water network structure is studied. Since the telemetry system has been applied increasingly in the water network, and in order to reflect the network operational condition more accurately, a new water network macroscopic model is developed by taking the auto-control adjusting valve opening state into consideration. Then for highly correlated or collinear independent variables in the model, the partial least squares (PLS) regression method provides a model solution which can distinguish between the system information and the noisy data. Finally, a hypothetical water network is introduced for validating the model. The simulation results show that the relative error is less than 5.2%, indicating that the model is efficient and feasible, and has better generalization performance.
基金This research receives funding from the Maryland Department of Transportation State Highway Administration.
文摘This paper studies the deterioration of bridge substructures utilizing the Long-Term Bridge Performance(LTBP)Program InfoBridge^(TM)and develops a survival model using Cox proportional hazards regression.The survival analysis is based on the National Bridge Inventory(NBI)dataset.The study calculates the survival rate of reinforced and prestressed concrete piles on bridges under marine conditions over a 29-year span(from 1992 to 2020).The state of Maryland is the primary focus of this study,with data from three neighboring regions,the District of Columbia,Virginia,and Delaware to expand the sample size.The data obtained from the National Bridge Inventory are condensed and filtered to acquire the most relevant information for model development.The Cox proportional hazards regression is applied to the condensed NBI data with six parameters:Age,ADT,ADTT,number of spans,span length,and structural length.Two survival models are generated for the bridge substructures:Reinforced and prestressed concrete piles in Maryland and reinforced and prestressed concrete piles in wet service conditions in the District of Columbia,Maryland,Delaware,and Virginia.Results from the Cox proportional hazards regression are used to construct Markov chains to demonstrate the sequence of the deterioration of bridge substructures.The Markov chains can be used as a tool to assist in the prediction and decision-making for repair,rehabilitation,and replacement of bridge piles.Based on the numerical model,the Pile Assessment Matrix Program(PAM)is developed to facilitate the assessment and maintenance of current bridge structures.The program integrates the NBI database with the inspection and research reports from various states’department of transportation,to serve as a tool for condition state simulation based on maintenance or rehabilitation strategies.
基金supported by the National Natural Science Foundation of China(Grant No 51767017)Gansu Province Basic Research Innovation Group Project(Grant No 18JR3RA133)+3 种基金Gansu Province Higher Education Industry Support and Guidance Project(Grant No 2022CYZC-22)Gansu Province Department of Ed-ucation Graduate Student’Innovation Star’Project(Grant No 2025CXZX-497)the Gansu Province Outstanding Doctoral Student Project(Grant No 25JRRA115)the Gansu Province Joint Research Foundation Major Program(Grant No 25JRRA1143).
文摘Wind turbine maintenance optimization faces challenges in balancing economic efficiency with operational reliability under environmental uncertainty.Traditional maintenance approaches exhibit limitations in adaptive decision-making,leading to increased operational costs and reliability risks.This study develops a physicsinformed reinforcement learning framework that integrates established domain knowledge with adaptive deci-sion algorithms.The approach embeds physical principles-including Weibull wind dynamics and multi-stage degradation models-into a reinforcement learning architecture,while introducing bidirectional temperature-degradation coupling for enhanced failure prediction.A high-fidelity simulation environment enables policy training through Proximal Policy Optimization,capturing complex interactions between environmental vari-ability and equipment deterioration.The framework was validated through case study implementation using northern China wind farm operational data.Results demonstrate zero-failure operation over simulated 19-year lifecycles,with economic performance improvements of 109.3%and 54.5%compared to conventional periodic and threshold-based maintenance strategies.By integrating physical constraints with intelligent algorithms,the method achieves adaptive maintenance decisions based on multi-dimensional state information.
