A mathematical model of principal elements of the aircraft hydraulic system is presented based on the heat transfer theory. The dynamic heat transfer process of the hydraulic oil and the pump shells within an aircraft...A mathematical model of principal elements of the aircraft hydraulic system is presented based on the heat transfer theory. The dynamic heat transfer process of the hydraulic oil and the pump shells within an aircraft hydraulic system are analyzed by the difference method. A kind of means for the prediction to variational trends of the aircraft hydraulic system temperature is provided during operation. The numerical prediction and simulation under the operational conditions are presented for ground trial running and the decelerated operation in flight. Computational results show that there is a good coincidence between the experimental data and the numerical predictions.展开更多
In this paper,the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method(DES),and the far-field noise is predicted using the Ffowcs Williams-Hawkings(FW-H)acoustic model.Th...In this paper,the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method(DES),and the far-field noise is predicted using the Ffowcs Williams-Hawkings(FW-H)acoustic model.The reliability of the numerical calculation is verified by wind tunnel experiments.The superposition relationship between the far-field radiated noise of the local aerodynamic noise sources of the high-speed train and the whole noise source is analyzed.Since the aerodynamic noise of high-speed trains is derived from its different components,a stepwise calculation method is proposed to predict the aerodynamic noise of high-speed trains.The results show that the local noise sources of high-speed trains and the whole noise source conform to the principle of sound source energy superposition.Using the head,middle and tail cars of the high-speed train as noise sources,different numerical models are established to obtain the far-field radiated noise of each aerodynamic noise source.The far-field total noise of high-speed trains is predicted using sound source superposition.A step-by-step calculation of each local aerodynamic noise source is used to obtain the superimposed value of the far-field noise.This is consistent with the far-field noise of the whole train model’s aerodynamic noise.The averaged sound pressure level of the far-field longitudinal noise measurement points differs by 1.92 dBA.The step-by-step numerical prediction method of aerodynamic noise of high-speed trains can provide a reference for the numerical prediction of aerodynamic noise generated by long marshalling high-speed trains.展开更多
The movement of Typhoon Maggie (9903) in June 1999 is one of the rare cases ever seen in the history. At 00U on June 6 Maggie was located at about 70 km to the southwest of Taiwan. When it arrived at the coastal regio...The movement of Typhoon Maggie (9903) in June 1999 is one of the rare cases ever seen in the history. At 00U on June 6 Maggie was located at about 70 km to the southwest of Taiwan. When it arrived at the coastal region of Shanwei City (22.8N, 116.5E), it turned suddenly to move southwestward along the southern China coastal line. De June 7 Maggie finally turned to move northward, making landfall to the north of Shangchuan Island. The experimental numerical prediction system on typhoon movement that was designed based on MM5 is proved quite successful for the 48h prediction of Maggie's movement and rainfall. The mean prediction error of typhoon track is 81 km for 0-24 h and 74 km for 24-48 h. The location of typhoon center in the initial field of the model is approximately 100 km away from the actual observations. In order to modify the location of typhoon center, a bogus typhoon was intro- duced into the model and the prediction of typhoon track was improved in 0-24 h time interval. But the prediction error was enlarged in 24-36 h. We also performed a sensitivity experiment of changing the land of southern China into the ocean. It is found that the orientation of South China coastal line and the topography have no obvious effect on the movement of Typhoon Maggie.展开更多
The‘Two Oceans and One Sea’area(West Pacific,Indian Ocean,and South China Sea;15°S–60°N,39°–178°E)is a core strategic area for the‘21st Century Maritime Silk Road’project,as well as national ...The‘Two Oceans and One Sea’area(West Pacific,Indian Ocean,and South China Sea;15°S–60°N,39°–178°E)is a core strategic area for the‘21st Century Maritime Silk Road’project,as well as national defense.With the increasing demand for disaster prevention and mitigation,the importance of 10–30-day extended range prediction,between the conventional short-term(around seven days)and the climate scale(longer than one month),is apparent.However,marine extended range prediction is still a‘blank point’in China,making the early warning of marine disasters almost impossible.Here,the authors introduce a recently launched Chinese national project on a numerical forecasting system for extended range prediction in the‘Two Oceans and One Sea’area based on a regional ultra-high resolution multi-layer coupled model,including the scientific aims,technical scheme,innovation,and expected achievements.The completion of this prediction system is of considerable significance for the economic development and national security of China.展开更多
In this paper,both measurements and numerical simulations of railway induced vibration are discussed.A measurement campaign has been carried out along the high-speed railway track in Lincent,Belgium.The experimental d...In this paper,both measurements and numerical simulations of railway induced vibration are discussed.A measurement campaign has been carried out along the high-speed railway track in Lincent,Belgium.The experimental determination of transfer functions and vibration velocity during train passages are discussed.A numerical model is introduced to predict the transfer functions and the vibration velocity during train passages.The comparison of experimental and numerical results demonstrates the importance of accurate numerical models and input data.The results are obtained in the framework of the development of a hybrid prediction method,where numerical and experimental data can be combined to improve the prediction accuracy for railway induced vibration.展开更多
A numerical simulation model for predicting residual stresses which arise during the solidification process of pressed glass bulb panel was developed. The solidification of a molten layer of glass between cooled paral...A numerical simulation model for predicting residual stresses which arise during the solidification process of pressed glass bulb panel was developed. The solidification of a molten layer of glass between cooled parallel plates was used to model the mechanics of the buildup of residual stresses in the forming process. A thermorheologically simple thermoviscoelastic model was assumed for the material. The finite element method employed was based on the theory of shells as an assembly of flat elements. This approach calculates residual stresses layer by layer like a truly three-dimensional calculation, which is well suited for thin pressed products of complex shape. An experimental comparison was employed to verify the proposed models and methods.展开更多
[Objective] The research aimed to analyze explanation effect of the European numerical prediction on temperature. [Method] Based on CMSVM regression method, by using 850 hPa grid point data of the European numerical p...[Objective] The research aimed to analyze explanation effect of the European numerical prediction on temperature. [Method] Based on CMSVM regression method, by using 850 hPa grid point data of the European numerical prediction from 2003 to 2009 and actual data of the maximum and minimum temperatures at 8 automatic stations in Qingyang City, prediction model of the temperature was established, and running effect of the business from 2008 to 2010 was tested and evaluated. [Result] The method had very good guidance role in real-time business running of the temperature prediction. Test and evaluation found that as forecast time prolonged, prediction accuracies of the maximum and minimum temperatures declined. When temperature anomaly was higher (actual temperature was higher than historical mean), prediction accuracy increased. Influence of the European numerical prediction was bigger. [Conclusion] Compared with other methods, operation of the prediction method was convenient, modeling was automatic, running time was short, system was stable, and prediction accuracy was high. It was suitable for implementing of the explanation work for numerical prediction product at meteorological station.展开更多
In this paper, on the basis of the heat conduction equation without consideration of the advection and turbulence effects, one-dimensional model for describing surface sea temperature ( T1), bottom sea temperature ( T...In this paper, on the basis of the heat conduction equation without consideration of the advection and turbulence effects, one-dimensional model for describing surface sea temperature ( T1), bottom sea temperature ( Tt ) and the thickness of the upper homogeneous layer ( h ) is developed in terms of the dimensionless temperature θT and depth η and self-simulation function θT - f(η) of vertical temperature profile by means of historical temperature data.The results of trial prediction with our one-dimensional model on T, Th, h , the thickness and gradient of thermocline are satisfactory to some extent.展开更多
During the '8th Five-Year Plan' (1991~1995), a new operational mesoscale numerical predictionsystem is developed, which is called the 'Regional Enhanced Numerical Prediction System'. The system possess...During the '8th Five-Year Plan' (1991~1995), a new operational mesoscale numerical predictionsystem is developed, which is called the 'Regional Enhanced Numerical Prediction System'. The system possesses higher resolution (45 km grid sise in horizontal, 10 layers in vertital), as well as fullphysical processes, and can be run operationally in the Guangzhou Regional Meteorological Centre(GRMC). A plenty of experiments indicate its better performance in predicting various weather systemsaffecting the south of China, especially the typhoon and heavy rain in the 'early floods stage' (annuallyspeaking). Verification of the prediction of all typhoon cases affecting the region in 1993~1995 indicatethat rainfall prediction scores of the system are obviously higher than those of the LAFS in the NationalMeteorological Centre, and track prediction error is no larger than those of NWPs in main world centressuch as the National Hurrieane Center of NOAA and the JMA. The aim of the paper is to give a generalized introduction and analysis to the system and its performance.展开更多
A mathematical formulation is applied to represent the phenomena in theincremental melting and solidification process (IMSP), and the temperature and electromagneticfields and the depth of steel liquid phase are calcu...A mathematical formulation is applied to represent the phenomena in theincremental melting and solidification process (IMSP), and the temperature and electromagneticfields and the depth of steel liquid phase are calculated by a finite difference technique using thecontrol volume method. The result shows that the predicted values are in good agreement with theobservations. In accordance with the calculated values for different kinds of materials anddifferent size of molds, the technological parameter of the IMS process such as the power supply andthe descending speed rate can be determined.展开更多
A dynamic numerical prediction model of sea water temperature for limited sea area is used to predict the sea water temperature at the sea area near Fujian. Essential adjustments have been made in accordance with the ...A dynamic numerical prediction model of sea water temperature for limited sea area is used to predict the sea water temperature at the sea area near Fujian. Essential adjustments have been made in accordance with the characteristics of this region. Two Tests have been made. One is in summer (3 d) and the other is in winter (10 d). In the summer test, a typhoon is just passing by and the calculated current field well responds to typhoon. In the winter test, variation tendency of the predicted sea water temperature field agrees with that of the observation basically, the absolute mean error in the whole sea area is 0 .6 ℃. The variation of the sea water temperature is mostly af- fected by entrainment and pumping, which is related to the topography of the strait.展开更多
Oceanic mesoscale circulations, primarily manifesting as eddies, typically span around 100 km horizontally and persist for about a month. These circulations represent the main component of oceanic kinetic energy and a...Oceanic mesoscale circulations, primarily manifesting as eddies, typically span around 100 km horizontally and persist for about a month. These circulations represent the main component of oceanic kinetic energy and are referred to as the“weather” of the ocean. Forecasting efforts, focused on periods from a day to a month, target these mesoscale circulations.Advances in eddy-resolving models, observing systems such as Argo floats and satellite altimeters, and data assimilation techniques have enabled systems like HYCOM in the United States and Mercator-Ocean in Europe to predict these features effectively. To further enhance mesoscale forecasting, the Pacific Regional Ocean Forecast System(RPOFS) was developed for the pan-western Pacific(100°E–178°E, 20°S–50°N). Covering the dynamic Kuroshio and Kuroshio Extension regions, RPOFS features a 3 km horizontal grid and 67 vertical levels, with a multi-scale three-dimensional variational data assimilation(MS-3DVAR) scheme implemented. This system assimilates data from various sources, including satellite sea surface height and temperature, as well as subsurface profiles. In particular, an enhanced altimeter data assimilation methodology allows explicitly constraining both barotropic and baroclinic components of sea surface height. RPOFS demonstrates reliable forecasting of mesoscale circulations, with five-day forecasts accurately predicting eddies larger than 150 km and capturing features of the Kuroshio large meander. Forecasting errors are comparable to or smaller than those of HYCOM and Mercator-Ocean systems.展开更多
Blasting is considered an indispensable process in mining excavation opera-tions.Generally,only a small percentage of the total energy of blasting is con-sumed in the fragmentation and displacement of the rock,and the...Blasting is considered an indispensable process in mining excavation opera-tions.Generally,only a small percentage of the total energy of blasting is con-sumed in the fragmentation and displacement of the rock,and the rest of the energy is transmitted to the structures and environment surrounding the mined area.The air overpressure(AOp)induced by explosions in open-cast mines has unavoidable environmental and safety consequences,but can be minimized to an acceptable threshold to limit environmental damage and the impact on the sustainability of mining activities.The development of numer-ical predictive models of AOp was the main objective of this study.Thus,the methodology used to achieve this main objective was articulated around six parts:knowledge of the study area,processing and statistical analysis of the data collected,development of both numerical and empirical prediction mod-els,and evaluation of model performance of the numerical model parameters.The results show that only numerical models are suitable for predicting AOp.Moreover,numerical models generally perform better than empirical models in predicting this phenomenon.Among these AI models,the results show that the DT model is the best suited for predicting AOp in this study,with remark-able performance results(RRSE of 0.08,RAE of 0.05,RMSE of 0.29,MAE of 0.37,MAPE of 0.07,and an R2 of 0.994).This could therefore justify its appli-cation in practical engineering to predict blast-induced AOp in open-cast mines to reduce undesirable environmental effects.展开更多
Systematic bias is a type of model error that can affect the accuracy of data assimilation and forecasting that must be addressed.An online bias correction scheme called the sequential bias correction scheme(SBCS),was...Systematic bias is a type of model error that can affect the accuracy of data assimilation and forecasting that must be addressed.An online bias correction scheme called the sequential bias correction scheme(SBCS),was developed using the6 h average bias to correct the systematic bias during model integration.The primary purpose of this study is to investigate the impact of the SBCS in the high-resolution China Meteorological Administration Meso-scale(CMA-MESO)numerical weather prediction(NWP)model to reduce the systematic bias and to improve the data assimilation and forecast results through this method.The SBCS is improved upon and applied to the CMA-MESO 3-km model in this study.Four-week sequential data assimilation and forecast experiments,driven by rapid update and cycling(RUC),were conducted for the period from 2–29 May 2022.In terms of the characteristics of systematic bias,both the background and analysis show diurnal bias,and these large biases are affected by complex underlying surfaces(e.g.,oceans,coasts,and mountains).After the application of the SBCS,the results of the data assimilation show that the SBCS can reduce the systematic bias of the background and yield a neutral to slightly positive result for the analysis fields.In addition,the SBCS can reduce forecast errors and improve forecast results,especially for surface variables.The above results indicate that this scheme has good prospects for high-resolution regional NWP models.展开更多
Accurate skin temperature is one of the critical factors in successfully assimilating satellite radiance data over land.However,model-simulated skin temperature may not be accurate enough.To address this issue,an exte...Accurate skin temperature is one of the critical factors in successfully assimilating satellite radiance data over land.However,model-simulated skin temperature may not be accurate enough.To address this issue,an extended skin temperature control variable(TSCV) approach is proposed in a variational assimilation framework,which also considers the background error correlation between skin temperature and atmospheric variables.A series of single observation tests and a 10-day cycling assimilation experiment were conducted to evaluate the impact of the TSCV approach on the assimilation of AMSU-A and ATMS(Advanced Technology Microwave Sounder) microwave temperature-sounding channels over land.The results of the single observation tests show that by applying the TSCV approach,not only the direct analysis of skin temperature is realized,but also the interaction between skin temperature and atmospheric variables can be achieved during the assimilation process.The results of the cycling experiment demonstrate that the TSCV approach improves the skin temperature analysis,which in turn reduces the RMSE of the surface variables and low-level air temperature forecasts.The TSCV approach also reduces the difference between the observed and simulated brightness temperatures of both microwave and infrared window channels over land,suggesting that the approach can facilitate the radiance simulation of these channels,thus contributing to the assimilation of window channels.展开更多
Due to various technical issues,existing numerical weather prediction(NWP)models often perform poorly at forecasting rainfall in the first several hours.To correct the bias of an NWP model and improve the accuracy of ...Due to various technical issues,existing numerical weather prediction(NWP)models often perform poorly at forecasting rainfall in the first several hours.To correct the bias of an NWP model and improve the accuracy of short-range precipitation forecasting,we propose a deep learning-based approach called UNet Mask,which combines NWP forecasts with the output of a convolutional neural network called UNet.The UNet Mask involves training the UNet on historical data from the NWP model and gridded rainfall observations for 6-hour precipitation forecasting.The overlap of the UNet output and the NWP forecasts at the same rainfall threshold yields a mask.The UNet Mask blends the UNet output and the NWP forecasts by taking the maximum between them and passing through the mask,which provides the corrected 6-hour rainfall forecasts.We evaluated UNet Mask on a test set and in real-time verification.The results showed that UNet Mask outperforms the NWP model in 6-hour precipitation prediction by reducing the FAR and improving CSI scores.Sensitivity tests also showed that different small rainfall thresholds applied to the UNet and the NWP model have different effects on UNet Mask's forecast performance.This study shows that UNet Mask is a promising approach for improving rainfall forecasting of NWP models.展开更多
Wind power generation is among the most promising and eco-friendly energy sources today. Wind Power Forecasting (WPF) is essential for boosting energy efficiency and maintaining the operational stability of power grid...Wind power generation is among the most promising and eco-friendly energy sources today. Wind Power Forecasting (WPF) is essential for boosting energy efficiency and maintaining the operational stability of power grids. However, predicting wind power comes with significant challenges, such as weather uncertainties, wind variability, complex terrain, limited data, insufficient measurement infrastructure, intricate interdependencies, and short lead times. These factors make it difficult to accurately forecast wind behavior and respond to sudden power output changes. This study aims to precisely forecast electricity generation from wind turbines, minimize grid operation uncertainties, and enhance grid reliability. It leverages historical wind farm data and Numerical Weather Prediction data, using k-Nearest Neighbors for pre-processing, K-means clustering for categorization, and Long Short-Term Memory (LSTM) networks for training and testing, with model performance evaluated across multiple metrics. The Grey Wolf Optimized (GWO) LSTM classification technique, a deep learning model suited to time series analysis, effectively handles temporal dependencies in input data through memory cells and gradient-based optimization. Inspired by grey wolves’ hunting strategies, GWO is a population-based metaheuristic optimization algorithm known for its strong performance across diverse optimization tasks. The proposed Grey Wolf Optimized Deep Learning model achieves an R-squared value of 0.97279, demonstrating that it explains 97.28% of the variance in wind power data. This model surpasses a reference study that achieved an R-squared value of 0.92 with a hybrid deep learning approach but did not account for outliers or anomalous data.展开更多
This paper presents the development of numerical prediction products(NPP) correction and display system(NPPCDS) for rapid and effective post-processing and displaying of the T213 NPP(numerical prediction products of t...This paper presents the development of numerical prediction products(NPP) correction and display system(NPPCDS) for rapid and effective post-processing and displaying of the T213 NPP(numerical prediction products of the medium range numerical weather prediction spectral model T213L31) through instant correction method. The NPPCDS consists of two modules: an automatic correction module and a graphical display module. The automatic correction module automatically corrects the T213 NPP at regularly scheduled time intervals, while the graphical display module interacts with users to display the T213 NPP and its correction results. The system helps forecasters extract the most relevant information at a quick glance without extensive post-processing. It is simple, easy to use, and computationally efficient, and has been running stably at Huludao Meteorological Bureau in Liaoning Province of China for the past three years. Because of its low computational costs, it is particularly useful for meteorological departments that lack advanced computing capacity and still need to make short-range weather forecasting.展开更多
The three-dimensional unsteady turbulent flow is studied numerically in the whole flow passage of hydraulic turbine, and vortex flow in the draft tube is predicted accurately in this paper. The numerical prediction is...The three-dimensional unsteady turbulent flow is studied numerically in the whole flow passage of hydraulic turbine, and vortex flow in the draft tube is predicted accurately in this paper. The numerical prediction is based on the Navier-Stokes equations and Large-Eddy Simulation （LES） model. The SIMPLE algorithm with the body fitted coordinate and tetrahedroid grid system is applied for the solution of the discretization governing equations.展开更多
Numerical simulation and 3-D periodic flow unsteadiness analysis for a centrifugal pump with volute are carried out in whole flow passage, including the impeller with twisted blades, the volute and the side chamber ch...Numerical simulation and 3-D periodic flow unsteadiness analysis for a centrifugal pump with volute are carried out in whole flow passage, including the impeller with twisted blades, the volute and the side chamber channels under a part-load condition. The pressure fluctuation intensity coefficient （PFIC） based on the standard deviation method, the time-averaged velocity unsteadiness intensity coefficient （VUIC） and the time-averaged turbulence intensity coefficient （TIC） are defined by averaging the results at each grid node for an entire impeller revolution period. Therefore, the strength distributions of the periodic flow unsteadiness based on the unsteady Reynolds-averaged Navier-Stokes （URANS） equations can be analyzed directly and in detail. It is shown that under the 0.6Qd~. condition, the pressure fluctuation intensity is larger near the blade pressure side than near the suction side, and a high fluctuation intensity can be observed at the beginning section of the spiral of the volute. The flow velocity unsteadiness intensity is larger near the blade suction side than near the pressure side. A strong turbulence intensity can be found near the blade suction side, the impeller shroud side as well as in the side chamber. The leakage flow has a significant effect on the inflow of the impeller, and can increase both the flow velocity unsteadiness intensity and the turbulence intensity near the wall. The accumulative flow unstea- diness results of an impeller revolution can be an important aspect to be considered in the centrifugal pump optimum design for obtaining a more stable inner flow of the pump and reducing the flow-induced vibration and noise in certain components.展开更多
文摘A mathematical model of principal elements of the aircraft hydraulic system is presented based on the heat transfer theory. The dynamic heat transfer process of the hydraulic oil and the pump shells within an aircraft hydraulic system are analyzed by the difference method. A kind of means for the prediction to variational trends of the aircraft hydraulic system temperature is provided during operation. The numerical prediction and simulation under the operational conditions are presented for ground trial running and the decelerated operation in flight. Computational results show that there is a good coincidence between the experimental data and the numerical predictions.
基金Supported by National Key Research and Development Program of China(Grant No.2020YFA0710902)National Natural Science Foundation of China(Grant No.12172308).
文摘In this paper,the unsteady flow around a high-speed train is numerically simulated by detached eddy simulation method(DES),and the far-field noise is predicted using the Ffowcs Williams-Hawkings(FW-H)acoustic model.The reliability of the numerical calculation is verified by wind tunnel experiments.The superposition relationship between the far-field radiated noise of the local aerodynamic noise sources of the high-speed train and the whole noise source is analyzed.Since the aerodynamic noise of high-speed trains is derived from its different components,a stepwise calculation method is proposed to predict the aerodynamic noise of high-speed trains.The results show that the local noise sources of high-speed trains and the whole noise source conform to the principle of sound source energy superposition.Using the head,middle and tail cars of the high-speed train as noise sources,different numerical models are established to obtain the far-field radiated noise of each aerodynamic noise source.The far-field total noise of high-speed trains is predicted using sound source superposition.A step-by-step calculation of each local aerodynamic noise source is used to obtain the superimposed value of the far-field noise.This is consistent with the far-field noise of the whole train model’s aerodynamic noise.The averaged sound pressure level of the far-field longitudinal noise measurement points differs by 1.92 dBA.The step-by-step numerical prediction method of aerodynamic noise of high-speed trains can provide a reference for the numerical prediction of aerodynamic noise generated by long marshalling high-speed trains.
文摘The movement of Typhoon Maggie (9903) in June 1999 is one of the rare cases ever seen in the history. At 00U on June 6 Maggie was located at about 70 km to the southwest of Taiwan. When it arrived at the coastal region of Shanwei City (22.8N, 116.5E), it turned suddenly to move southwestward along the southern China coastal line. De June 7 Maggie finally turned to move northward, making landfall to the north of Shangchuan Island. The experimental numerical prediction system on typhoon movement that was designed based on MM5 is proved quite successful for the 48h prediction of Maggie's movement and rainfall. The mean prediction error of typhoon track is 81 km for 0-24 h and 74 km for 24-48 h. The location of typhoon center in the initial field of the model is approximately 100 km away from the actual observations. In order to modify the location of typhoon center, a bogus typhoon was intro- duced into the model and the prediction of typhoon track was improved in 0-24 h time interval. But the prediction error was enlarged in 24-36 h. We also performed a sensitivity experiment of changing the land of southern China into the ocean. It is found that the orientation of South China coastal line and the topography have no obvious effect on the movement of Typhoon Maggie.
基金supported by the National Key Research and Development Program of China(Grant Nos.2017YFC1404105,2017YFC1404100,2017YFC1404101,2017YFC1404102,2017YFC1404103 and 2017YFC1404104)
文摘The‘Two Oceans and One Sea’area(West Pacific,Indian Ocean,and South China Sea;15°S–60°N,39°–178°E)is a core strategic area for the‘21st Century Maritime Silk Road’project,as well as national defense.With the increasing demand for disaster prevention and mitigation,the importance of 10–30-day extended range prediction,between the conventional short-term(around seven days)and the climate scale(longer than one month),is apparent.However,marine extended range prediction is still a‘blank point’in China,making the early warning of marine disasters almost impossible.Here,the authors introduce a recently launched Chinese national project on a numerical forecasting system for extended range prediction in the‘Two Oceans and One Sea’area based on a regional ultra-high resolution multi-layer coupled model,including the scientific aims,technical scheme,innovation,and expected achievements.The completion of this prediction system is of considerable significance for the economic development and national security of China.
文摘In this paper,both measurements and numerical simulations of railway induced vibration are discussed.A measurement campaign has been carried out along the high-speed railway track in Lincent,Belgium.The experimental determination of transfer functions and vibration velocity during train passages are discussed.A numerical model is introduced to predict the transfer functions and the vibration velocity during train passages.The comparison of experimental and numerical results demonstrates the importance of accurate numerical models and input data.The results are obtained in the framework of the development of a hybrid prediction method,where numerical and experimental data can be combined to improve the prediction accuracy for railway induced vibration.
基金Project supported by the National Natural Science Foundation of China (No.50205011)
文摘A numerical simulation model for predicting residual stresses which arise during the solidification process of pressed glass bulb panel was developed. The solidification of a molten layer of glass between cooled parallel plates was used to model the mechanics of the buildup of residual stresses in the forming process. A thermorheologically simple thermoviscoelastic model was assumed for the material. The finite element method employed was based on the theory of shells as an assembly of flat elements. This approach calculates residual stresses layer by layer like a truly three-dimensional calculation, which is well suited for thin pressed products of complex shape. An experimental comparison was employed to verify the proposed models and methods.
文摘[Objective] The research aimed to analyze explanation effect of the European numerical prediction on temperature. [Method] Based on CMSVM regression method, by using 850 hPa grid point data of the European numerical prediction from 2003 to 2009 and actual data of the maximum and minimum temperatures at 8 automatic stations in Qingyang City, prediction model of the temperature was established, and running effect of the business from 2008 to 2010 was tested and evaluated. [Result] The method had very good guidance role in real-time business running of the temperature prediction. Test and evaluation found that as forecast time prolonged, prediction accuracies of the maximum and minimum temperatures declined. When temperature anomaly was higher (actual temperature was higher than historical mean), prediction accuracy increased. Influence of the European numerical prediction was bigger. [Conclusion] Compared with other methods, operation of the prediction method was convenient, modeling was automatic, running time was short, system was stable, and prediction accuracy was high. It was suitable for implementing of the explanation work for numerical prediction product at meteorological station.
文摘In this paper, on the basis of the heat conduction equation without consideration of the advection and turbulence effects, one-dimensional model for describing surface sea temperature ( T1), bottom sea temperature ( Tt ) and the thickness of the upper homogeneous layer ( h ) is developed in terms of the dimensionless temperature θT and depth η and self-simulation function θT - f(η) of vertical temperature profile by means of historical temperature data.The results of trial prediction with our one-dimensional model on T, Th, h , the thickness and gradient of thermocline are satisfactory to some extent.
文摘During the '8th Five-Year Plan' (1991~1995), a new operational mesoscale numerical predictionsystem is developed, which is called the 'Regional Enhanced Numerical Prediction System'. The system possesses higher resolution (45 km grid sise in horizontal, 10 layers in vertital), as well as fullphysical processes, and can be run operationally in the Guangzhou Regional Meteorological Centre(GRMC). A plenty of experiments indicate its better performance in predicting various weather systemsaffecting the south of China, especially the typhoon and heavy rain in the 'early floods stage' (annuallyspeaking). Verification of the prediction of all typhoon cases affecting the region in 1993~1995 indicatethat rainfall prediction scores of the system are obviously higher than those of the LAFS in the NationalMeteorological Centre, and track prediction error is no larger than those of NWPs in main world centressuch as the National Hurrieane Center of NOAA and the JMA. The aim of the paper is to give a generalized introduction and analysis to the system and its performance.
文摘A mathematical formulation is applied to represent the phenomena in theincremental melting and solidification process (IMSP), and the temperature and electromagneticfields and the depth of steel liquid phase are calculated by a finite difference technique using thecontrol volume method. The result shows that the predicted values are in good agreement with theobservations. In accordance with the calculated values for different kinds of materials anddifferent size of molds, the technological parameter of the IMS process such as the power supply andthe descending speed rate can be determined.
基金The project was financially supported by the Natural Science Foundation of Province under contract No. Q99E02 andthe special f
文摘A dynamic numerical prediction model of sea water temperature for limited sea area is used to predict the sea water temperature at the sea area near Fujian. Essential adjustments have been made in accordance with the characteristics of this region. Two Tests have been made. One is in summer (3 d) and the other is in winter (10 d). In the summer test, a typhoon is just passing by and the calculated current field well responds to typhoon. In the winter test, variation tendency of the predicted sea water temperature field agrees with that of the observation basically, the absolute mean error in the whole sea area is 0 .6 ℃. The variation of the sea water temperature is mostly af- fected by entrainment and pumping, which is related to the topography of the strait.
基金supported by the National Key R&D Program of China (Grant No. 2022YFF0801404)the National Natural Science Foundation of China (Grant No. 42192552)。
文摘Oceanic mesoscale circulations, primarily manifesting as eddies, typically span around 100 km horizontally and persist for about a month. These circulations represent the main component of oceanic kinetic energy and are referred to as the“weather” of the ocean. Forecasting efforts, focused on periods from a day to a month, target these mesoscale circulations.Advances in eddy-resolving models, observing systems such as Argo floats and satellite altimeters, and data assimilation techniques have enabled systems like HYCOM in the United States and Mercator-Ocean in Europe to predict these features effectively. To further enhance mesoscale forecasting, the Pacific Regional Ocean Forecast System(RPOFS) was developed for the pan-western Pacific(100°E–178°E, 20°S–50°N). Covering the dynamic Kuroshio and Kuroshio Extension regions, RPOFS features a 3 km horizontal grid and 67 vertical levels, with a multi-scale three-dimensional variational data assimilation(MS-3DVAR) scheme implemented. This system assimilates data from various sources, including satellite sea surface height and temperature, as well as subsurface profiles. In particular, an enhanced altimeter data assimilation methodology allows explicitly constraining both barotropic and baroclinic components of sea surface height. RPOFS demonstrates reliable forecasting of mesoscale circulations, with five-day forecasts accurately predicting eddies larger than 150 km and capturing features of the Kuroshio large meander. Forecasting errors are comparable to or smaller than those of HYCOM and Mercator-Ocean systems.
文摘Blasting is considered an indispensable process in mining excavation opera-tions.Generally,only a small percentage of the total energy of blasting is con-sumed in the fragmentation and displacement of the rock,and the rest of the energy is transmitted to the structures and environment surrounding the mined area.The air overpressure(AOp)induced by explosions in open-cast mines has unavoidable environmental and safety consequences,but can be minimized to an acceptable threshold to limit environmental damage and the impact on the sustainability of mining activities.The development of numer-ical predictive models of AOp was the main objective of this study.Thus,the methodology used to achieve this main objective was articulated around six parts:knowledge of the study area,processing and statistical analysis of the data collected,development of both numerical and empirical prediction mod-els,and evaluation of model performance of the numerical model parameters.The results show that only numerical models are suitable for predicting AOp.Moreover,numerical models generally perform better than empirical models in predicting this phenomenon.Among these AI models,the results show that the DT model is the best suited for predicting AOp in this study,with remark-able performance results(RRSE of 0.08,RAE of 0.05,RMSE of 0.29,MAE of 0.37,MAPE of 0.07,and an R2 of 0.994).This could therefore justify its appli-cation in practical engineering to predict blast-induced AOp in open-cast mines to reduce undesirable environmental effects.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2242213,U2142213,42305167,42175105)。
文摘Systematic bias is a type of model error that can affect the accuracy of data assimilation and forecasting that must be addressed.An online bias correction scheme called the sequential bias correction scheme(SBCS),was developed using the6 h average bias to correct the systematic bias during model integration.The primary purpose of this study is to investigate the impact of the SBCS in the high-resolution China Meteorological Administration Meso-scale(CMA-MESO)numerical weather prediction(NWP)model to reduce the systematic bias and to improve the data assimilation and forecast results through this method.The SBCS is improved upon and applied to the CMA-MESO 3-km model in this study.Four-week sequential data assimilation and forecast experiments,driven by rapid update and cycling(RUC),were conducted for the period from 2–29 May 2022.In terms of the characteristics of systematic bias,both the background and analysis show diurnal bias,and these large biases are affected by complex underlying surfaces(e.g.,oceans,coasts,and mountains).After the application of the SBCS,the results of the data assimilation show that the SBCS can reduce the systematic bias of the background and yield a neutral to slightly positive result for the analysis fields.In addition,the SBCS can reduce forecast errors and improve forecast results,especially for surface variables.The above results indicate that this scheme has good prospects for high-resolution regional NWP models.
基金sponsored by the National Natural Science Foundation of China(Grant No.42075148)the High-Performance Computing Center of Nanjing University of Information Science & Technology for supporting this work。
文摘Accurate skin temperature is one of the critical factors in successfully assimilating satellite radiance data over land.However,model-simulated skin temperature may not be accurate enough.To address this issue,an extended skin temperature control variable(TSCV) approach is proposed in a variational assimilation framework,which also considers the background error correlation between skin temperature and atmospheric variables.A series of single observation tests and a 10-day cycling assimilation experiment were conducted to evaluate the impact of the TSCV approach on the assimilation of AMSU-A and ATMS(Advanced Technology Microwave Sounder) microwave temperature-sounding channels over land.The results of the single observation tests show that by applying the TSCV approach,not only the direct analysis of skin temperature is realized,but also the interaction between skin temperature and atmospheric variables can be achieved during the assimilation process.The results of the cycling experiment demonstrate that the TSCV approach improves the skin temperature analysis,which in turn reduces the RMSE of the surface variables and low-level air temperature forecasts.The TSCV approach also reduces the difference between the observed and simulated brightness temperatures of both microwave and infrared window channels over land,suggesting that the approach can facilitate the radiance simulation of these channels,thus contributing to the assimilation of window channels.
基金jointly supported by the National Natural Science Foundation of China(Grant No.U1811464)the Hydraulic Innovation Project of Science and Technology of Guangdong Province of China(Grant No.2022-01)the Guangzhou Basic and Applied Basic Research Foundation(Grant No.202201011472)。
文摘Due to various technical issues,existing numerical weather prediction(NWP)models often perform poorly at forecasting rainfall in the first several hours.To correct the bias of an NWP model and improve the accuracy of short-range precipitation forecasting,we propose a deep learning-based approach called UNet Mask,which combines NWP forecasts with the output of a convolutional neural network called UNet.The UNet Mask involves training the UNet on historical data from the NWP model and gridded rainfall observations for 6-hour precipitation forecasting.The overlap of the UNet output and the NWP forecasts at the same rainfall threshold yields a mask.The UNet Mask blends the UNet output and the NWP forecasts by taking the maximum between them and passing through the mask,which provides the corrected 6-hour rainfall forecasts.We evaluated UNet Mask on a test set and in real-time verification.The results showed that UNet Mask outperforms the NWP model in 6-hour precipitation prediction by reducing the FAR and improving CSI scores.Sensitivity tests also showed that different small rainfall thresholds applied to the UNet and the NWP model have different effects on UNet Mask's forecast performance.This study shows that UNet Mask is a promising approach for improving rainfall forecasting of NWP models.
文摘Wind power generation is among the most promising and eco-friendly energy sources today. Wind Power Forecasting (WPF) is essential for boosting energy efficiency and maintaining the operational stability of power grids. However, predicting wind power comes with significant challenges, such as weather uncertainties, wind variability, complex terrain, limited data, insufficient measurement infrastructure, intricate interdependencies, and short lead times. These factors make it difficult to accurately forecast wind behavior and respond to sudden power output changes. This study aims to precisely forecast electricity generation from wind turbines, minimize grid operation uncertainties, and enhance grid reliability. It leverages historical wind farm data and Numerical Weather Prediction data, using k-Nearest Neighbors for pre-processing, K-means clustering for categorization, and Long Short-Term Memory (LSTM) networks for training and testing, with model performance evaluated across multiple metrics. The Grey Wolf Optimized (GWO) LSTM classification technique, a deep learning model suited to time series analysis, effectively handles temporal dependencies in input data through memory cells and gradient-based optimization. Inspired by grey wolves’ hunting strategies, GWO is a population-based metaheuristic optimization algorithm known for its strong performance across diverse optimization tasks. The proposed Grey Wolf Optimized Deep Learning model achieves an R-squared value of 0.97279, demonstrating that it explains 97.28% of the variance in wind power data. This model surpasses a reference study that achieved an R-squared value of 0.92 with a hybrid deep learning approach but did not account for outliers or anomalous data.
基金Under the auspices of National Natural Science Foundation of China(No.91125010)
文摘This paper presents the development of numerical prediction products(NPP) correction and display system(NPPCDS) for rapid and effective post-processing and displaying of the T213 NPP(numerical prediction products of the medium range numerical weather prediction spectral model T213L31) through instant correction method. The NPPCDS consists of two modules: an automatic correction module and a graphical display module. The automatic correction module automatically corrects the T213 NPP at regularly scheduled time intervals, while the graphical display module interacts with users to display the T213 NPP and its correction results. The system helps forecasters extract the most relevant information at a quick glance without extensive post-processing. It is simple, easy to use, and computationally efficient, and has been running stably at Huludao Meteorological Bureau in Liaoning Province of China for the past three years. Because of its low computational costs, it is particularly useful for meteorological departments that lack advanced computing capacity and still need to make short-range weather forecasting.
基金Project supported by the National Natural Science Foundation of China (Grant No :50179021) and the Youth Scienceand Technology Foundation of Sichuan (Grant No :05ZQ026-07) .
文摘The three-dimensional unsteady turbulent flow is studied numerically in the whole flow passage of hydraulic turbine, and vortex flow in the draft tube is predicted accurately in this paper. The numerical prediction is based on the Navier-Stokes equations and Large-Eddy Simulation （LES） model. The SIMPLE algorithm with the body fitted coordinate and tetrahedroid grid system is applied for the solution of the discretization governing equations.
基金supported by the National Natural Science Foun-dation of China(Grant Nos.51239005,51009072)the National Science and Technology Pillar Program of China(Grant No.2011BAF14B04)
文摘Numerical simulation and 3-D periodic flow unsteadiness analysis for a centrifugal pump with volute are carried out in whole flow passage, including the impeller with twisted blades, the volute and the side chamber channels under a part-load condition. The pressure fluctuation intensity coefficient （PFIC） based on the standard deviation method, the time-averaged velocity unsteadiness intensity coefficient （VUIC） and the time-averaged turbulence intensity coefficient （TIC） are defined by averaging the results at each grid node for an entire impeller revolution period. Therefore, the strength distributions of the periodic flow unsteadiness based on the unsteady Reynolds-averaged Navier-Stokes （URANS） equations can be analyzed directly and in detail. It is shown that under the 0.6Qd~. condition, the pressure fluctuation intensity is larger near the blade pressure side than near the suction side, and a high fluctuation intensity can be observed at the beginning section of the spiral of the volute. The flow velocity unsteadiness intensity is larger near the blade suction side than near the pressure side. A strong turbulence intensity can be found near the blade suction side, the impeller shroud side as well as in the side chamber. The leakage flow has a significant effect on the inflow of the impeller, and can increase both the flow velocity unsteadiness intensity and the turbulence intensity near the wall. The accumulative flow unstea- diness results of an impeller revolution can be an important aspect to be considered in the centrifugal pump optimum design for obtaining a more stable inner flow of the pump and reducing the flow-induced vibration and noise in certain components.
