Engineering tests can yield inaccurate data due to instrument errors,human factors,and environmental interference,introducing uncertainty in numerical model updating.This study employs the probability-box(p-box)method...Engineering tests can yield inaccurate data due to instrument errors,human factors,and environmental interference,introducing uncertainty in numerical model updating.This study employs the probability-box(p-box)method for representing observational uncertainty and develops a two-step approximate Bayesian computation(ABC)framework using time-series data.Within the ABC framework,Euclidean and Bhattacharyya distances are employed as uncertainty quantification metrics to delineate approximate likelihood functions in the initial and subsequent steps,respectively.A novel variational Bayesian Monte Carlo method is introduced to efficiently apply the ABC framework amidst observational uncertainty,resulting in rapid convergence and accurate parameter estimation with minimal iterations.The efficacy of the proposed updating strategy is validated by its application to a shear frame model excited by seismic wave and an aviation pump force sensor for thermal output analysis.The results affirm the efficiency,robustness,and practical applicability of the proposed method.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
Fractures play a crucial role in various fields such as hydrocarbon exploration,groundwater resources management,and earthquake research.The determination of fracture location and the estimation of parameters such as ...Fractures play a crucial role in various fields such as hydrocarbon exploration,groundwater resources management,and earthquake research.The determination of fracture location and the estimation of parameters such as fracture length and dip angle are the focus of geophysical work.In borehole observation system,the short distance between fractures and detectors leads to weak attenuation of elastic wave energy,and high-frequency source makes it easier to identify small-scale fractures.Compared to traditional monopole logging methods,dipole logging method has advantage of exciting pure shear waves sensitive to fractures,so its application is becoming increasingly widespread.However,since the reflected shear waves and scattered shear waves of fractures correspond to different fracture properties,how to distinguish and analyze these two kinds of waves is crucial for accurately characterizing the fracture parameters.To address this issue,numerical simulation of wave responses by a single fracture near a borehole in rock formation is performed,and the generation mechanism and characteristics of shear waves scattered by fractures are investigated.It is found that when the dip angle of the fracture surpasses a critical threshold,the S-wave will propagate to both endpoints of the fracture and generate scattered S-waves,resulting in two distinct scattered wave packets on the received waveform.When the polarization direction of the acoustic source is parallel to the strike of the fracture,the scattered SH-waves always have larger amplitude than the scattered SV-waves regardless of changing the fracture dip angle.Unlike SV-waves,the SH-waves scattered by the fracture do not have any mode conversion.Additionally,propagation of S-waves to a short length fracture can induce dipole mode vibration of the fracture within a wide frequency range.The phenomena of shear waves reflected and scattered by the fracture are further illustrated and verified by two field examples,thus showing the potential of scattered waves for fracture evaluation and characterization with borehole observation system.展开更多
Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation...Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.展开更多
The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typic...The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typically input multiple time slices without deterministic dependencies.In this study,the CNOP for DLMs(CNOP-DL)is proposed as an extension of the CNOP in the time dimension.This method is useful for targeted observations as it indicates not only where but also when to deploy additional observations.The CNOP-DL is calculated for a forecast case of sea surface temperature in the South China Sea with a DLM.The CNOP-DL identifies a sensitive area northwest of Palawan Island at the last input time.Sensitivity experiments demonstrate that the sensitive area identified by the CNOP-DL is effective not only for the CNOP-DL itself,but also for random perturbations.Therefore,this approach holds potential for guiding practical field campaigns.Notably,forecast errors are more sensitive to time than to location in the sensitive area.It highlights the crucial role of identifying the time of the sensitive area in targeted observations,corroborating the usefulness of extending the CNOP in the time dimension.展开更多
Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on chang...Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on changes of flow regime characteristics remained rare.This study detects temporal changes in 16 flow regime metrics from five main components(i.e.,magnitude,frequency of events,variability,duration,and timing),and evaluates the effects of observation uncertainty on trends of flow regime metrics by adopting a normal distribution error model and using uncertainty width,significant change rate of slopes,coefficient of variation,and degree of deviation.The daily runoff series from 1971 to 2020 at five hydrological stations(i.e.,Huangheyan,Tangnaihai,and Lanzhou in the Yellow River Source Region,Xianyang in the Weihe River Catchment,and Heishiguan in the Yiluo River Catchment)in the water conservation zone of Yellow River are collected for our study.Results showed that:(1)Flow regimes showed significant increases in the low flow magnitude,and significant decreases in the high and average flow magnitude,variability and duration at all the five stations.The magnitude,variability and duration metrics decreased significantly,and the frequency metrics increased significantly at Heishiguan.The low flow magnitude and timing metrics increased significantly,while the high flow magnitude,frequency and variability metrics decreased significantly at Xianyang.The low flow magnitude and high flow timing metrics increased significantly,while the low flow frequency,high flow magnitude and variability metrics decreased significantly in the Yellow River Source Region.(2)Observation uncertainty remarkably impacted the changes of 28.75% of total flow regime metrics at all the stations.The trends of 11.25% of total metrics changed from significance to insignificance,while those of 17.5% of total metrics changed from insignificance to significance.For the rest metrics,the trends remained the same,i.e.,significant(18.75%)and insignificant(52.50%)trends.(3)Observation uncertainty had the greatest impacts on the frequency metrics,especially at Xianyang,followed by duration,variability,timing and magnitude metrics.展开更多
The effect of the wide and narrow azimuth 3D observation systems on seismic imaging precision is becoming a hot area for studies of high precision 3D seismic acquisition methods in recent years. In this paper we utili...The effect of the wide and narrow azimuth 3D observation systems on seismic imaging precision is becoming a hot area for studies of high precision 3D seismic acquisition methods in recent years. In this paper we utilize 3D physical seismic modeling experiments. A 3D channel sand body physical seismic model is constructed and two acquisition systems are designed with wide azimuth （16 lines） and narrow azimuth （8 lines） to model 3D seismic data acquisition and processing seismic work flows. From analysis of migrated time slice data with high quality and small size, we conclude that when the overlying layers are smooth and lateral velocities have little change, both wide and narrow azimuth observation systems in 3D acquisition can be used for obtaining high precision imaging and equivalent resolution of the channel sand body.展开更多
A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership fu...A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership functions. In the FORBFNN model, the weight coefficients of nodes in the hidden layer are identified by using the fuzzy expectation-maximization （ EM ） algorithm, whereas the optimal number of these nodes as well as the centers and widths of radial basis functions are automatically constructed by using a data-driven method. Namely, the method starts with an initial node, and then a new node is added in a hidden layer according to some rules. This procedure is not terminated until the model meets the preset requirements. The method considers both the accuracy and complexity of the model. Numerical simulation results show that the modeling method is effective, and the established model has high prediction accuracy.展开更多
Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind s...Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind speed, is of great significance to identify ice drift characteristics. A sea ice substitute, the so-called "modelled ice", which is made by polypropylene material with a density similar to Bohai Sea ice, is used to complete a free drift experiment in the open sea. The trajectories of isolated modelled ice, currents and wind in the Bohai Sea during non-frozen and frozen periods are obtained. The results show that the currents play a major role while the wind plays a minor role in the free drift of isolated modelled ice when the wind is mild in the Bohai Sea. The modelled ice drift is significantly affected by the ocean current and wind based on the ice–current–wind relationship established by a multiple linear regression. The modelled ice velocity calculated by the multiple linear regression is close to that of the in situ observation, the magnitude of the error between the calculated and observed ice velocities is less than12.05%, and the velocity direction error is less than 6.21°. Thus, the ice velocity can be estimated based on the observed current velocity and wind speed when the in situ observed ice velocity is missing. And the modelled ice of same thickness with a smaller density is more sensitive to the current velocity and the wind speed changes. In addition, the modelled ice drift characteristics are shown to be close to those of the real sea ice, which indicates that the modelled ice can be used as a good substitute of real ice for in situ observation of the free ice drift in the open sea, which helps solve time availability, safety and logistics problems related to in situ observation on real ice.展开更多
Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolu...Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.展开更多
The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehi...The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle＇s roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system（ESC）. The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model＇s generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal （the magnitude up to 1°）, followed by the longitudinal acceleration-deceleration and the road wave amplitude （the magnitude up to 0.3°）. Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.展开更多
This paper based on the essay [1], studies in case that replicated observations are available in some experimental points., the parameters estimation of one dimensional linear errors-in-variables (EV) models. Asymptot...This paper based on the essay [1], studies in case that replicated observations are available in some experimental points., the parameters estimation of one dimensional linear errors-in-variables (EV) models. Asymptotic normality is established.展开更多
The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and tempora...The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO_2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO_2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO_2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model's performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO_2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within-0.3 and 1.3 ppm, except for inland stations(7.7 ppm).展开更多
In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic...In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic priority. However,the priority of the imaging task is dynamic in actual engineering. To supplement the research on imaging observation, this paper proposes the task priority model, dynamic scheduling strategy and Heuristic algorithm. At first, this paper analyzes the relevant theoretical basis of imaging observation, decomposes the task priority into four parts, including target priority, imaging task priority, track, telemetry & control(TT&C)requirement priority and data transmission requirement priority, summarizes the attribute factors that affect the above four types of priority in detail, and designs the corresponding priority model. Then, this paper takes the emergency tasks scheduling problem as the background, proposes the dynamic scheduling strategy and heuristic algorithm. Finally, the task priority model,dynamic scheduling strategy and heuristic algorithm are verified by experiments.展开更多
In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angu...In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angular observation model to integrate observations from UAV and mobile mapping vehicle platform,realizing a joint,coordinated observation operation from both air and ground.We develop a multi-source remote sensing data acquisition system to effectively acquire multi-angle data of complex urban scenes.Multi-source data fusion solves the missing data problem caused by occlusion and achieves accurate,rapid,and complete collection of holographic spatial and temporal information in complex urban scenes.We carried out an experiment on Baisha Town,Chongqing,China and obtained multi-sensor,multi-angle data from UAV and mobile mapping vehicle.We first extracted the point cloud from UAV and then integrated the UAV and mobile mapping vehicle point cloud.The inte-grated results combined both the characteristics of UAV and mobile mapping vehicle point cloud,confirming the practicability of the proposed joint data acquisition platform and the effectiveness of spatio-temporal-spectral-angular observation model.Compared with the observation from UAV or mobile mapping vehicle alone,the integrated system provides an effective data acquisition solution toward comprehensive urban monitoring.展开更多
The initial solidification process of microalloyed steels was simulated using a confocal scanning laser microscope,and the growth behavior of austenite grain was observed in situ.The method for measuring the initial a...The initial solidification process of microalloyed steels was simulated using a confocal scanning laser microscope,and the growth behavior of austenite grain was observed in situ.The method for measuring the initial austenite grain size was studied,and the M_(0)^(*)(the parameter to describe the grain boundary migration)values at different cooling rates were then calculated using the initial austenite grain size and the final grain size.Next,a newly modified model for predicting the austenite grain size was established by introducing the relationship between M_(0)^(*)and the cooling rate,and the value calculated from the modified model closely corresponds to the measured value,with average relative error being less than 5%.Further,the relationship between T^(γ)(the starting temperature for austenite grain growth)and equivalent carbon content C_(P)(C_(P)>0.18%)was obtained by in situ observation,and it was introduced into the modified model,which expanded the application scope of the model.Taking the continuous casting slab produced by a steel plant as the experimental object,the modified austenite grain size prediction model was used to predict the austenite grain size at different depths of oscillation mark on the surface of slab,and the predicted value was in good agreement with the actual measured value.展开更多
This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-thresho...This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.展开更多
In the paper, the kinematic model of tectonic blocks in southwest China is studied based on the precision GPS observations carried out under the major subject of 'Studies on Current Crustal Movement and Geodynamic...In the paper, the kinematic model of tectonic blocks in southwest China is studied based on the precision GPS observations carried out under the major subject of 'Studies on Current Crustal Movement and Geodynamics' which belongs to the State Climbing Project. It is believed that at present, the data of high precision GPS observation may provide convincing information related to the horizontal movement of tectonic blocks in the Chinese mainland. The preliminary results obtained from the kinematic model have given some direct evidences for the research of dynamic mechanism of crustal deformation in the Chinese mainland and on the basis of which, the kinematic characteristics and their relations to the seismicity and seismic risk in the reobserved region are analysed. The preliminary observation results are encouraging.展开更多
The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation acc...The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation accuracy and therefore navigation accuracy.Additionally,the conventional observation model（COM）used by the filter may be divergent,which would result into some terrible accuracies of INS/GPS integration navigation in some cases.To improve the navigation accuracy,the linearization accuracy of the COM still needs further improvement.To deal with this issue,the observation model is modified with the linearization of the range and range rate equations in this paper.Compared with COM,the modified observation model（MOM）further considers the difference between the real user position and the position calculated by SINS.To verify the advantages of this model,INS/GPS integrated navigation simulation experiments are conducted with the usage of COM and MOM respectively.According to the simulation results,the positions（velocities）calculated using COM are divergent over time while the others using MOM are convergent,which demonstrates the higher linearization accuracy of MOM.展开更多
This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transm...This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transmitting multi-media frames to create observer-dependent realities. Key aspects include deriving frame rates, defining quantum reality, and establishing hierarchical observer structures. The model’s impact on quantum information theory and philosophical interpretations of reality are examined, with detailed discussions on information loss and recursive frame transmission in the appendices.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.U23B20105).
文摘Engineering tests can yield inaccurate data due to instrument errors,human factors,and environmental interference,introducing uncertainty in numerical model updating.This study employs the probability-box(p-box)method for representing observational uncertainty and develops a two-step approximate Bayesian computation(ABC)framework using time-series data.Within the ABC framework,Euclidean and Bhattacharyya distances are employed as uncertainty quantification metrics to delineate approximate likelihood functions in the initial and subsequent steps,respectively.A novel variational Bayesian Monte Carlo method is introduced to efficiently apply the ABC framework amidst observational uncertainty,resulting in rapid convergence and accurate parameter estimation with minimal iterations.The efficacy of the proposed updating strategy is validated by its application to a shear frame model excited by seismic wave and an aviation pump force sensor for thermal output analysis.The results affirm the efficiency,robustness,and practical applicability of the proposed method.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
基金supported by Scientific Research and Technology Development Project of CNPC(2024ZG38,2024ZG42)the CNPC Innovation Fund(2022DQ02-0307).
文摘Fractures play a crucial role in various fields such as hydrocarbon exploration,groundwater resources management,and earthquake research.The determination of fracture location and the estimation of parameters such as fracture length and dip angle are the focus of geophysical work.In borehole observation system,the short distance between fractures and detectors leads to weak attenuation of elastic wave energy,and high-frequency source makes it easier to identify small-scale fractures.Compared to traditional monopole logging methods,dipole logging method has advantage of exciting pure shear waves sensitive to fractures,so its application is becoming increasingly widespread.However,since the reflected shear waves and scattered shear waves of fractures correspond to different fracture properties,how to distinguish and analyze these two kinds of waves is crucial for accurately characterizing the fracture parameters.To address this issue,numerical simulation of wave responses by a single fracture near a borehole in rock formation is performed,and the generation mechanism and characteristics of shear waves scattered by fractures are investigated.It is found that when the dip angle of the fracture surpasses a critical threshold,the S-wave will propagate to both endpoints of the fracture and generate scattered S-waves,resulting in two distinct scattered wave packets on the received waveform.When the polarization direction of the acoustic source is parallel to the strike of the fracture,the scattered SH-waves always have larger amplitude than the scattered SV-waves regardless of changing the fracture dip angle.Unlike SV-waves,the SH-waves scattered by the fracture do not have any mode conversion.Additionally,propagation of S-waves to a short length fracture can induce dipole mode vibration of the fracture within a wide frequency range.The phenomena of shear waves reflected and scattered by the fracture are further illustrated and verified by two field examples,thus showing the potential of scattered waves for fracture evaluation and characterization with borehole observation system.
基金supported by the National Natural Science Foundation of China[grant number 42175132]the National Key R&D Program[grant number 2020YFA0607802]the CAS Information Technology Program[grant number CAS-WX2021SF-0107-02]。
文摘Solar energy is a pivotal clean energy source in the transition to carbon neutrality from fossil fuels.However,the intermittent and stochastic characteristics of solar radiation pose challenges for accurate simulation and prediction.Accurately simulating and predicting solar radiation and its variability are crucial for optimizing solar energy utilization.This study conducted simulation experiments using the WRF-Solar model from 25 June to 25 July 2022,to evaluate the accuracy and performance of the simulated solar radiation across China.The simulations covered the whole country with a grid spacing of 27 km and were compared with ground observation network data from the Chinese Ecosystem Research Network.The results indicated that WRF-Solar can accurately capture the spatiotemporal patterns of global horizontal irradiance over China,but there is still an overestimation of solar radiation,and the model underestimates the total cloud cover.The root-mean-square error ranged from 92.83 to 188.13 W m^(-2) and the mean bias(MB)ranged from 21.05 to 56.22 W m^(-2).The simulation showed the smallest MB at Lhasa on the Qinghai–Tibet Plateau,while the largest MB was observed in Southeast China.To enhance the accuracy of solar radiation simulation,the authors compared the Fast All-sky Radiation Model for Solar with the Rapid Radiative Transfer Model for General Circulation Models and found that the former provides better simulation.
基金supported by the National Natural Science Foundation of China (Grant No. 42288101, 42375062, 42476192, 42275158)the National Key Scientific and Technological Infrastructure project “Earth System Science Numerical Simulator Facility” (Earth Lab)the GHfund C (202407036001)
文摘The Conditional Nonlinear Optimal Perturbation(CNOP)method works essentially for conventional numerical models;however,it is not fully applicable to the commonly used deep-learning forecasting models(DLMs),which typically input multiple time slices without deterministic dependencies.In this study,the CNOP for DLMs(CNOP-DL)is proposed as an extension of the CNOP in the time dimension.This method is useful for targeted observations as it indicates not only where but also when to deploy additional observations.The CNOP-DL is calculated for a forecast case of sea surface temperature in the South China Sea with a DLM.The CNOP-DL identifies a sensitive area northwest of Palawan Island at the last input time.Sensitivity experiments demonstrate that the sensitive area identified by the CNOP-DL is effective not only for the CNOP-DL itself,but also for random perturbations.Therefore,this approach holds potential for guiding practical field campaigns.Notably,forecast errors are more sensitive to time than to location in the sensitive area.It highlights the crucial role of identifying the time of the sensitive area in targeted observations,corroborating the usefulness of extending the CNOP in the time dimension.
基金National Key Research and Development Program of China,No.2021YFC3201102National Natural Science Foundation of China,No.42071041,No.42171047。
文摘Runoff observation uncertainty is a key unsolved issue in the hydrology community.Existing studies mainly focused on observation uncertainty sources and their impacts on simulation performance,but the impacts on changes of flow regime characteristics remained rare.This study detects temporal changes in 16 flow regime metrics from five main components(i.e.,magnitude,frequency of events,variability,duration,and timing),and evaluates the effects of observation uncertainty on trends of flow regime metrics by adopting a normal distribution error model and using uncertainty width,significant change rate of slopes,coefficient of variation,and degree of deviation.The daily runoff series from 1971 to 2020 at five hydrological stations(i.e.,Huangheyan,Tangnaihai,and Lanzhou in the Yellow River Source Region,Xianyang in the Weihe River Catchment,and Heishiguan in the Yiluo River Catchment)in the water conservation zone of Yellow River are collected for our study.Results showed that:(1)Flow regimes showed significant increases in the low flow magnitude,and significant decreases in the high and average flow magnitude,variability and duration at all the five stations.The magnitude,variability and duration metrics decreased significantly,and the frequency metrics increased significantly at Heishiguan.The low flow magnitude and timing metrics increased significantly,while the high flow magnitude,frequency and variability metrics decreased significantly at Xianyang.The low flow magnitude and high flow timing metrics increased significantly,while the low flow frequency,high flow magnitude and variability metrics decreased significantly in the Yellow River Source Region.(2)Observation uncertainty remarkably impacted the changes of 28.75% of total flow regime metrics at all the stations.The trends of 11.25% of total metrics changed from significance to insignificance,while those of 17.5% of total metrics changed from insignificance to significance.For the rest metrics,the trends remained the same,i.e.,significant(18.75%)and insignificant(52.50%)trends.(3)Observation uncertainty had the greatest impacts on the frequency metrics,especially at Xianyang,followed by duration,variability,timing and magnitude metrics.
基金supported by the National Basic Research Program (the 973 Program, No. 2007CB209601).
文摘The effect of the wide and narrow azimuth 3D observation systems on seismic imaging precision is becoming a hot area for studies of high precision 3D seismic acquisition methods in recent years. In this paper we utilize 3D physical seismic modeling experiments. A 3D channel sand body physical seismic model is constructed and two acquisition systems are designed with wide azimuth （16 lines） and narrow azimuth （8 lines） to model 3D seismic data acquisition and processing seismic work flows. From analysis of migrated time slice data with high quality and small size, we conclude that when the overlying layers are smooth and lateral velocities have little change, both wide and narrow azimuth observation systems in 3D acquisition can be used for obtaining high precision imaging and equivalent resolution of the channel sand body.
基金The National Natural Science Foundation of China(No.51106025,51106027,51036002)Specialized Research Fund for the Doctoral Program of Higher Education(No.20130092110061)the Youth Foundation of Nanjing Institute of Technology(No.QKJA201303)
文摘A fuzzy observations-based radial basis function neural network （FORBFNN） is presented for modeling nonlinear systems in which the observations of response are imprecise but can be represented as fuzzy membership functions. In the FORBFNN model, the weight coefficients of nodes in the hidden layer are identified by using the fuzzy expectation-maximization （ EM ） algorithm, whereas the optimal number of these nodes as well as the centers and widths of radial basis functions are automatically constructed by using a data-driven method. Namely, the method starts with an initial node, and then a new node is added in a hidden layer according to some rules. This procedure is not terminated until the model meets the preset requirements. The method considers both the accuracy and complexity of the model. Numerical simulation results show that the modeling method is effective, and the established model has high prediction accuracy.
基金The National Natural Science Foundation of China under contract No.41571510the Fundamental Research Funds for the Central Universities of China under contract No.2014KJJCB02
文摘Sea ice drift is mainly controlled by ocean currents, local wind, and internal ice stress. Information on sea ice motion, especially in situ synchronous observation of an ice velocity, a current velocity, and a wind speed, is of great significance to identify ice drift characteristics. A sea ice substitute, the so-called "modelled ice", which is made by polypropylene material with a density similar to Bohai Sea ice, is used to complete a free drift experiment in the open sea. The trajectories of isolated modelled ice, currents and wind in the Bohai Sea during non-frozen and frozen periods are obtained. The results show that the currents play a major role while the wind plays a minor role in the free drift of isolated modelled ice when the wind is mild in the Bohai Sea. The modelled ice drift is significantly affected by the ocean current and wind based on the ice–current–wind relationship established by a multiple linear regression. The modelled ice velocity calculated by the multiple linear regression is close to that of the in situ observation, the magnitude of the error between the calculated and observed ice velocities is less than12.05%, and the velocity direction error is less than 6.21°. Thus, the ice velocity can be estimated based on the observed current velocity and wind speed when the in situ observed ice velocity is missing. And the modelled ice of same thickness with a smaller density is more sensitive to the current velocity and the wind speed changes. In addition, the modelled ice drift characteristics are shown to be close to those of the real sea ice, which indicates that the modelled ice can be used as a good substitute of real ice for in situ observation of the free ice drift in the open sea, which helps solve time availability, safety and logistics problems related to in situ observation on real ice.
基金This work is supported by the National Key Research and Development Program of China[grant number 2018YFB2100501]the Key Research and Development Program of Yunnan province in China[grant number 2018IB023]+2 种基金the Research Project from the Ministry of Natural Resources of China[grant number 4201⁃⁃240100123]the National Natural Science Foundation of China[grant numbers 41771452,41771454,41890820,and 41901340]the Natural Science Fund of Hubei Province in China[grant number 2018CFA007].
文摘Taking cities as objects being observed,urban remote sensing is an important branch of remote sensing.Given the complexity of the urban scenes,urban remote sensing observation requires data with a high temporal resolution,high spatial resolution,and high spectral resolution.To the best of our knowledge,however,no satellite owns all the above character-istics.Thus,it is necessary to coordinate data from existing remote sensing satellites to meet the needs of urban observation.In this study,we abstracted the urban remote sensing observation process and proposed an urban spatio-temporal-spectral observation model,filling the gap of no existing urban remote sensing framework.In this study,we present four applications to elaborate on the specific applications of the proposed model:1)a spatiotemporal fusion model for synthesizing ideal data,2)a spatio-spectral observation model for urban vegetation biomass estimation,3)a temporal-spectral observation model for urban flood mapping,and 4)a spatio-temporal-spectral model for impervious surface extraction.We believe that the proposed model,although in a conceptual stage,can largely benefit urban observation by providing a new data fusion paradigm.
基金supported by National Natural Science Foundation of China(Grant No.51105001)State Key Laboratory of Automotive Safety and Energy,Tsinghua University,China(Grant No.KF14022)
文摘The current research of real-time observation for vehicle roll steer angle and compliance steer angle（both of them comprehensively referred as the additional steer angle in this paper） mainly employs the linear vehicle dynamic model, in which only the lateral acceleration of vehicle body is considered. The observation accuracy resorting to this method cannot meet the requirements of vehicle real-time stability control, especially under extreme driving conditions. The paper explores the solution resorting to experimental method. Firstly, a multi-body dynamic model of a passenger car is built based on the ADAMS/Car software, whose dynamic accuracy is verified by the same vehicle＇s roadway test data of steady static circular test. Based on this simulation platform, several influencing factors of additional steer angle under different driving conditions are quantitatively analyzed. Then ε-SVR algorithm is employed to build the additional steer angle prediction model, whose input vectors mainly include the sensor information of standard electronic stability control system（ESC）. The method of typical slalom tests and FMVSS 126 tests are adopted to make simulation, train model and test model＇s generalization performance. The test result shows that the influence of lateral acceleration on additional steer angle is maximal （the magnitude up to 1°）, followed by the longitudinal acceleration-deceleration and the road wave amplitude （the magnitude up to 0.3°）. Moreover, both the prediction accuracy and the calculation real-time of the model can meet the control requirements of ESC This research expands the accurate observation methods of the additional steer angle under extreme driving conditions.
基金the National Natural Science Foundation of China (Grant No. 19631040)
文摘This paper based on the essay [1], studies in case that replicated observations are available in some experimental points., the parameters estimation of one dimensional linear errors-in-variables (EV) models. Asymptotic normality is established.
基金supported by the Korea Meteorological Administration Research and Development Program "Research and Development for KMA Weather, and Earth system Services-Development and Assessment of AR6 Climate Change Scenarios" under Grant (KMA2018-00321)
文摘The CarbonTracker(CT) model has been used in previous studies for understanding and predicting the sources, sinks, and dynamics that govern the distribution of atmospheric CO_2 at varying ranges of spatial and temporal scales. However, there are still challenges for reproducing accurate model-simulated CO_2 concentrations close to the surface, typically associated with high spatial heterogeneity and land cover. In the present study, we evaluated the performance of nested-grid CT model simulations of CO_2 based on the CT2016 version through comparison with in-situ observations over East Asia covering the period 2009–13. We selected sites located in coastal, remote, inland, and mountain areas. The results are presented at diurnal and seasonal time periods. At target stations, model agreement with in-situ observations was varied in capturing the diurnal cycle. Overall, biases were less than 6.3 ppm on an all-hourly mean basis, and this was further reduced to a maximum of 4.6 ppm when considering only the daytime. For instance, at Anmyeondo, a small bias was obtained in winter, on the order of 0.2 ppm. The model revealed a diurnal amplitude of CO_2 that was nearly flat in winter at Gosan and Anmyeondo stations, while slightly overestimated in the summertime. The model's performance in reproducing the diurnal cycle remains a challenge and requires improvement. The model showed better agreement with the observations in capturing the seasonal variations of CO_2 during daytime at most sites, with a correlation coefficient ranging from 0.70 to 0.99. Also, model biases were within-0.3 and 1.3 ppm, except for inland stations(7.7 ppm).
基金supported by the National Natural Science Foundation of China(61773120,61473301,71501180,71501179,61603400)。
文摘In the imaging observation system, imaging task scheduling is an important topic. Most scholars study the imaging task scheduling from the perspective of static priority, and only a few from the perspective of dynamic priority. However,the priority of the imaging task is dynamic in actual engineering. To supplement the research on imaging observation, this paper proposes the task priority model, dynamic scheduling strategy and Heuristic algorithm. At first, this paper analyzes the relevant theoretical basis of imaging observation, decomposes the task priority into four parts, including target priority, imaging task priority, track, telemetry & control(TT&C)requirement priority and data transmission requirement priority, summarizes the attribute factors that affect the above four types of priority in detail, and designs the corresponding priority model. Then, this paper takes the emergency tasks scheduling problem as the background, proposes the dynamic scheduling strategy and heuristic algorithm. Finally, the task priority model,dynamic scheduling strategy and heuristic algorithm are verified by experiments.
基金This work is supported by the National Natural Science Foundation of China[grant numbers 42090012,41771452,41771454,and 41901340].
文摘In a complex urban scene,observation from a single sensor unavoidably leads to voids in observations,failing to describe urban objects in a comprehensive manner.In this paper,we propose a spatio-temporal-spectral-angular observation model to integrate observations from UAV and mobile mapping vehicle platform,realizing a joint,coordinated observation operation from both air and ground.We develop a multi-source remote sensing data acquisition system to effectively acquire multi-angle data of complex urban scenes.Multi-source data fusion solves the missing data problem caused by occlusion and achieves accurate,rapid,and complete collection of holographic spatial and temporal information in complex urban scenes.We carried out an experiment on Baisha Town,Chongqing,China and obtained multi-sensor,multi-angle data from UAV and mobile mapping vehicle.We first extracted the point cloud from UAV and then integrated the UAV and mobile mapping vehicle point cloud.The inte-grated results combined both the characteristics of UAV and mobile mapping vehicle point cloud,confirming the practicability of the proposed joint data acquisition platform and the effectiveness of spatio-temporal-spectral-angular observation model.Compared with the observation from UAV or mobile mapping vehicle alone,the integrated system provides an effective data acquisition solution toward comprehensive urban monitoring.
基金the Joint Fund of Iron and Steel Research of the National Natural Science Foundation of China and Baowu Group Corporation(Grant No.U1760103).
文摘The initial solidification process of microalloyed steels was simulated using a confocal scanning laser microscope,and the growth behavior of austenite grain was observed in situ.The method for measuring the initial austenite grain size was studied,and the M_(0)^(*)(the parameter to describe the grain boundary migration)values at different cooling rates were then calculated using the initial austenite grain size and the final grain size.Next,a newly modified model for predicting the austenite grain size was established by introducing the relationship between M_(0)^(*)and the cooling rate,and the value calculated from the modified model closely corresponds to the measured value,with average relative error being less than 5%.Further,the relationship between T^(γ)(the starting temperature for austenite grain growth)and equivalent carbon content C_(P)(C_(P)>0.18%)was obtained by in situ observation,and it was introduced into the modified model,which expanded the application scope of the model.Taking the continuous casting slab produced by a steel plant as the experimental object,the modified austenite grain size prediction model was used to predict the austenite grain size at different depths of oscillation mark on the surface of slab,and the predicted value was in good agreement with the actual measured value.
基金This work was supported by the National Natural Science Foundation of China(62076025).
文摘This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.
文摘In the paper, the kinematic model of tectonic blocks in southwest China is studied based on the precision GPS observations carried out under the major subject of 'Studies on Current Crustal Movement and Geodynamics' which belongs to the State Climbing Project. It is believed that at present, the data of high precision GPS observation may provide convincing information related to the horizontal movement of tectonic blocks in the Chinese mainland. The preliminary results obtained from the kinematic model have given some direct evidences for the research of dynamic mechanism of crustal deformation in the Chinese mainland and on the basis of which, the kinematic characteristics and their relations to the seismicity and seismic risk in the reobserved region are analysed. The preliminary observation results are encouraging.
基金Supported by the National Natural Science Foundation of China(61502257,41304031)
文摘The conventional Kalman filter（CKF）is widely used in tightly-coupled INS/GPS integrated navigation systems.The linearization accuracy of the CKF observation model is one of the decisive factors of the estimation accuracy and therefore navigation accuracy.Additionally,the conventional observation model（COM）used by the filter may be divergent,which would result into some terrible accuracies of INS/GPS integration navigation in some cases.To improve the navigation accuracy,the linearization accuracy of the COM still needs further improvement.To deal with this issue,the observation model is modified with the linearization of the range and range rate equations in this paper.Compared with COM,the modified observation model（MOM）further considers the difference between the real user position and the position calculated by SINS.To verify the advantages of this model,INS/GPS integrated navigation simulation experiments are conducted with the usage of COM and MOM respectively.According to the simulation results,the positions（velocities）calculated using COM are divergent over time while the others using MOM are convergent,which demonstrates the higher linearization accuracy of MOM.
文摘This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transmitting multi-media frames to create observer-dependent realities. Key aspects include deriving frame rates, defining quantum reality, and establishing hierarchical observer structures. The model’s impact on quantum information theory and philosophical interpretations of reality are examined, with detailed discussions on information loss and recursive frame transmission in the appendices.
