Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybr...Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.展开更多
In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statist...In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.展开更多
This study aims to explore the impact of combined health education and dietary guidance on the speed of postoperative recovery in patients with gastrointestinal polyps.A specific number of patients who underwent gastr...This study aims to explore the impact of combined health education and dietary guidance on the speed of postoperative recovery in patients with gastrointestinal polyps.A specific number of patients who underwent gastrointestinal polyp resection were selected and randomly divided into a control group and an experimental group.The control group received routine nursing,while the experimental group implemented combined health education and dietary guidance on this basis.By comparing the recovery indicators of the two groups,it was found that the recovery speed of the experimental group was significantly faster than that of the control group,indicating that this combined intervention method can effectively promote patient recovery.展开更多
During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the i...During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.展开更多
Wind speed is a crucial parameter affecting wind energy utilization.However,its volatility leads to time-varying power output.Herein,a novel Seq2Seq model integrating deep learning,data denoising,and a shape-aware los...Wind speed is a crucial parameter affecting wind energy utilization.However,its volatility leads to time-varying power output.Herein,a novel Seq2Seq model integrating deep learning,data denoising,and a shape-aware loss function is proposed for accurate multistep wind speed forecasting.In this model,the wind speed data is first denoised using the maximal overlap discrete wavelet transform.Next,an encoder-decoder network based on a temporal convolutional network,bidirectional gated recurrent unit,and multihead self-attention is employed for forecasting.Additionally,to enhance the ability of the model to identify temporal dynamics,a shape-aware loss function,ITILDE-Q,is employed in the model.To verify the effectiveness of the proposed model,a comparative experiment and an ablation experiment were conducted using three datasets of measured wind speeds.Three error metrics and a similarity metric were adopted for comprehensive evaluation.The experimental results showed that the proposed model consistently outperforms benchmark models in all tested forecasting scenarios,with particularly pronounced differences in performance over longer forecast horizons.Furthermore,the synergistic interaction of the three key components contributes to the extraordinary performance of the proposed model.展开更多
Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning...Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning to mitigate accuracy degradation in 24-h forecasting.Initially,an optimized DB-SCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm clusters wind fields based on wind direction,probability density,and spectral features,enhancing physical interpretability and reducing training complexity.Subsequently,a ResNet(Residual Network)extracts multi-scale patterns from decomposed wind signals,while transfer learning adapts the backbone network across clusters,cutting training time by over 90%.Finally,a CBAM(Convolutional Block Attention Module)attention mechanism is employed to prioritize features for LSTM-based prediction.Tested on the 2015 Jena wind speed dataset,the model demonstrates superior accuracy and robustness compared to state-of-the-art baselines.Key innovations include:(a)Physics-informed clustering for interpretable wind regime classification;(b)Transfer learning with deep feature extraction,preserving accuracy while minimizing training time;and(c)On the 2016 Jena wind speed dataset,the model achieves MAPE(Mean Absolute Percentage Error)values of 16.82%and 18.02%for the Weibull-shaped and Gaussian-shaped wind speed clusters,respectively,demonstrating the model’s robust generalization capacity.This framework offers an efficient and effective solution for long-term wind forecasting.展开更多
Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the...Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).展开更多
The dual challenges of critical speed prediction inaccuracies and ambiguous vibration behaviors are present in high-speed flexible rotors,particularly in free turbine rotors in turboshaft engine systems.The study begi...The dual challenges of critical speed prediction inaccuracies and ambiguous vibration behaviors are present in high-speed flexible rotors,particularly in free turbine rotors in turboshaft engine systems.The study begins with an examination of the rotor-bearing bidirectional coupling mechanism,with a primary focus on the nonlinear characteristics of the bearing.An investigation is carried out on the mechanical modeling methodologies for four-point contact ball bearings(FPCBBs)and cylindrical roller bearings(CRBs).To address the issue of excessive computational time in traditional bearing calculation methods,the sled dog optimization(SDO)algorithm is substituted for the conventional Newton-Raphson method.A rotor-bearing coupling dynamics model is developed by the finite element and lumped mass methods,with experimental validation achieved through a simulator test rig.The effects of three internal bearing parameters in FPCBBs(arching width and raceway groove curvature coefficient)and CRBs(initial radial clearance)on the critical speed characteristics and vibrational behavior of rotorbearing coupled systems are examined.The numerical simulation results show some interesting conclusions.展开更多
In this paper,a novel guidance law is proposed which can achieve the desired impact speed and angle simultaneously for unpowered gliding vehicles.A guidance law with only impact angle constraint is used to produce the...In this paper,a novel guidance law is proposed which can achieve the desired impact speed and angle simultaneously for unpowered gliding vehicles.A guidance law with only impact angle constraint is used to produce the guidance profile,and its convergence in the varying speed scenario is proved.A relationship between flight states,guidance input and impact speed is established.By applying the fixed-time convergence control theory of error dynamics,an impact speed corrector is built with the above guidance profile,which can implement impact speed correction without affecting the impact angle constraint.Numerical simulations with various impact speed and angle constraints are conducted to demonstrate the performance of the proposed guidance law,and the robustness is also verified by Monte Carlo tests.展开更多
Enhancing the mining speed of a working face has become the primary approach to achieve high production and efficiency in coal mines,thereby further improving the production capacity.However,the problem of rock bursts...Enhancing the mining speed of a working face has become the primary approach to achieve high production and efficiency in coal mines,thereby further improving the production capacity.However,the problem of rock bursts resulting from this approach has become increasingly serious.Therefore,to implement coal mine safety and efficient extraction,the impact of deformation pressure caused by different mining speeds should be considered,and a reasonable mining speed of the working face should be determined.The influence of mining speed on overlying rock breaking in the stope is analyzed by establishing a key layer block rotation and subsidence model.Results show that with the increasing mining speed,the compression amount of gangue in the goaf decreases,and the rotation and subsidence amount of rock block B above goaf decreases,forcing the rotation and subsidence amount of rock block A above roadway to increase.Consequently,the contact mode between rock block A and rock block B changes from line contact to point contact,and the horizontal thrust and shear force between blocks increase.The increase in rotation and subsidence of rock block A intensifies the compression degree of coal and rock mass below the key layer,thereby increasing the stress concentration degree of coal and rock mass as well as the total energy accumulation.In addition,due to the insufficient compression of gangue in the goaf,the bending and subsidence space of the far-field key layer are limited,the length of the suspended roof increases,and the influence range of mining stress and the energy accumulation range expand.Numerical test results and underground microseismic monitoring results verify the correlation between mining speed and stope energy,and high-energy events generally appear 1-2 d after the change in mining speed.On this basis,the statistical principle confirms that the maximum mining speed of the working face at 6 m/d is reasonable.展开更多
To reveal the rock burst mechanism,the stress and failure characteristics of coal-rock strata under different advancing speeds of mining working face were explored by theoretical analysis,simulation,and engineering mo...To reveal the rock burst mechanism,the stress and failure characteristics of coal-rock strata under different advancing speeds of mining working face were explored by theoretical analysis,simulation,and engineering monitoring.The relationship between energy accumulation and release was analyzed,and a reasonable mining speed according to specific projects was recommended.The theoretical analysis shows that as the mining speed increases from 4 to 15 m/d,the rheological coefficient of coal mass ranges from 0.9 to 0.4,and the elastic energy of coal mass accumulation varies from 100 to 900 kJ.Based on the simulation,there is a critical advancing speed,the iteration numbers of simulation are less than 15,000 per mining 10 m coal seam,the overburden structure is obvious,the abutment pressure in coal mass is large,and the accumulated energy is large,which is easy to cause strong rock burst.When the iteration number is greater than 15,000,the static force of coal mass increases slightly,but there is no obvious rock burst.Based on engineering monitoring,the mining speed of a mine is less than 8 m/d,and the periodic weighting distance is about 17 m;as the mining speed is greater than 10 m/d,and the periodic weighting distance is greater than 20 m;as the mining speed is 3-8 m/d,and the range of high stress in surrounding rock is 48 m;as the advancing speed is 8-12 m/d,and the high-stress range in surrounding rock is 80 m.Moreover,as the mining speed is less than 8 cut cycles,the micro seismic energy is less than 10,000 J;as the mining speed is 12 cut cycles,the microseismic energy is about 20,000 J.In summary,the advancing speed is positively correlated with the micro seismic event;as the mining speed increases,the accumulated elastic energy of surrounding rock is greater,which is easy to cause rock burst.The comprehensive analysis indicates the daily advance speed of the mine is not more than 12 cut cycles.展开更多
Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford...Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.展开更多
This paper deals with the monotonicity of limit wave speed c0(h)to a perturbed g KdV equation.We show the decrease of c0(h)by combining the analytic method and the numerical technique.Our results solve a special case ...This paper deals with the monotonicity of limit wave speed c0(h)to a perturbed g KdV equation.We show the decrease of c0(h)by combining the analytic method and the numerical technique.Our results solve a special case of the open question presented by Yan et al.,and the method potentially provides a way to study the monotonicity of c0(h)for general m∈N^(+).展开更多
Ultrasound computed tomography(USCT)is a noninvasive biomedical imaging modality that offers insights into acoustic properties such as the sound speed(SS)and acoustic attenuation(AA)of the human body,enhancing diagnos...Ultrasound computed tomography(USCT)is a noninvasive biomedical imaging modality that offers insights into acoustic properties such as the sound speed(SS)and acoustic attenuation(AA)of the human body,enhancing diagnostic accuracy and therapy planning.Full waveform inversion(FWI)is a promising USCT image reconstruction method that optimizes the parameter fields of a wave propagation model via gradient-based optimization.However,twodimensional FWI methods are limited by their inability to account for three-dimensional wave propagation in the elevation direction,resulting in image artifacts.To address this problem,we propose a three-dimensional time-domain full waveform inversion algorithm to reconstruct the SS and AA distributions on the basis of a fractional Laplacian wave equation,adjoint field formulation,and gradient descent optimization.Validated by two sets of simulations,the proposed algorithm has potential for generating high-resolution and quantitative SS and AA distributions.This approach holds promise for clinical USCT applications,assisting early disease detection,precise abnormality localization,and optimized treatment planning,thus contributing to better healthcare outcomes.展开更多
Application of variable speed limits(VSL)is gradually increasingly implemented especially on highways.As a result of conducted studies and implementations,it is observed that the variable speed limits have reduced the...Application of variable speed limits(VSL)is gradually increasingly implemented especially on highways.As a result of conducted studies and implementations,it is observed that the variable speed limits have reduced the number of car accidents as well as proved positive results in terms of delays and environmental factors.Purpose of this study is to develop an algorithm for VSL application that is considered to be applied on Istanbul D100 highway and to assess the effects of application.Algorithm that is developed for VSL is a different VSL algorithm and compared with the constant speed system.According to obtained results,when the proposed system is compared to current system,it is observed that the number of delays and average stops are reduced%30 and%40 respectively and also emissions reduced at the rate of%12.展开更多
When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is...When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.展开更多
This paper explores the development of interpretable data elements from raw data using Kolmogorov-Arnold Networks(KAN).With the exponential growth of data in contemporary society,there is an urgent need for effective ...This paper explores the development of interpretable data elements from raw data using Kolmogorov-Arnold Networks(KAN).With the exponential growth of data in contemporary society,there is an urgent need for effective data processing methods to unlock the full potential of this resource.The study focuses on the application of KAN in the transportation sector to transform raw traffic data into meaningful data elements.The core of the research is the KANT-GCN model,which synergizes Kolmogorov-Arnold Networks with Temporal Graph Convolutional Networks(T-GCN).This innovative model demonstrates superior performance in predicting traffic speeds,outperforming existing methods in terms of accuracy,reliability,and interpretability.The model was evaluated using real-world datasets from Shenzhen,Los Angeles,and the San Francisco Bay Area,showing significant improvements in different metrics.The paper highlights the potential of KAN-T-GCN to revolutionize data-driven decision-making in traffic management and other sectors,underscoring its ability to handle dynamic updates and maintain data integrity.展开更多
Sea-surface wind is a vital meteorological element in marine activities and climate research.This study proposed the spectral attention enhanced multidimensional feature fusion convolutional long short-term memory(LST...Sea-surface wind is a vital meteorological element in marine activities and climate research.This study proposed the spectral attention enhanced multidimensional feature fusion convolutional long short-term memory(LSTM)network(SAMFF-Conv-LSTM),a novel approach for sea-surface wind-speed prediction that emphasizes the temporal characteristics of data samples.The model incorporates the Fourier transform to extract time-and frequency-domain features from wave and wind variables.For the 12 h prediction,the SAMFF-ConvLSTM achieved a correlation coefficient of 0.960 and a root mean square error(RMSE)of 1.350 m/s,implying a high prediction accuracy.For the 24 h prediction,the RMSE of the SAMFF-ConvLSTM was reduced by 38.11%,14.26%,and 13.36%compared with those of the convolutional neural network,gated recurrent units,and convolutional LSTM(ConvLSTM),respectively.These results confirm the superior reliability and accuracy of the SAMFF-ConvLSTM over traditional models in theoretical and practical applications.展开更多
This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward...This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward spreading speeds for the infective individuals, which can be used to estimate how fast the disease spreads. To overcome the difficulty arising from the lack of comparison principle for such time-space periodic nonmonotone systems, our proof is mainly based on constructing a series of scalar time-space periodic equations, establishing the spreading speeds for such auxiliary equations and using comparison methods. It may be the first work to study the spreading speed for time-space periodic non-monotone systems.展开更多
By applying the convolution-based Hilbert transform in the zonal direction on six-hourly streamfunction fields at200 h Pa, we present the climatology and trends of the local wave period, and zonal and meridional phase...By applying the convolution-based Hilbert transform in the zonal direction on six-hourly streamfunction fields at200 h Pa, we present the climatology and trends of the local wave period, and zonal and meridional phase speeds, of Rossby waves over the globe during the solstice seasons of 1979–2023. While partly similar to and inspired by Fragkoulidis and Wirth(2020), our method differs in its ability to cover both planetary-scale and synoptic-scale waves over not only the extratropics, but also the tropics and subtropics. Based on a physically reasonable global distribution of wave periods, our key new finding is a robust prolonging of wave periods over most regions of the tropics and subtropics during both solstice seasons of 1979–2023, except for the tropical Atlantic, which experiences a shortened wave period during June–July–August of 1979–2022. Both the prolonging and shortening of wave periods are mainly associated with the changes in planetary-scale waves. Regionally varying trends of the zonal phase speed(Cpx) of synoptic waves are consistent in sign with, but smaller in magnitude than, the trends of local zonal wind, confirming the conclusion of Wu and Lu(2023)on the opposite effects of zonal wind and the meridional gradient of potential vorticity on Cpx. Meanwhile, the Cpx trends of planetary-scale waves are relatively weak, and do not exhibit a robust relation with the trend of zonal wind. These new results are helpful toward better understanding the changes in atmospheric waves and extreme events under global warming.展开更多
文摘Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.
基金supported by the Key Laboratory of South China Sea Meteorological Disaster Prevention and Mitigation of Hainan Province(No.SCSF202307)the Basic Research Fund of CAMS(No.2023Z016)+1 种基金the National Natural Scientific Foundation of China(No.42275037)the Jiangsu Collaborative Innovation Center for Climate Change。
文摘In this study,tropical cyclone(TC)translation speed was introduced as a new similarity factor within the generalized initial value(GIV)framework,enhancing the disaster preassessment capability of the dynamical statistical analog ensemble forecast model for landfalling TC disasters(DSAEF_LTD model).Three TC translation speed indicators most relevant to TC precipitation were incorporated:the maximum speed on Day 1(the first day of TC-induced precipitation and wind occurring on land)and the average and minimum speeds over All Days(all days of TC-induced precipitation and wind occurring on land),all classified using the Kmeans clustering algorithm.Simulation experiments showed that integrating TC translation speed enhanced the model's performance.The model provided a better optimal common scheme,with the TSS UM(sum of threat scores for severe and above and extremely severe and above disasters)increasing by 2.66%(from 0.5117 to 0.5253)compared with the original model.More importantly,its preassessment ability improved significantly,with the average TSS UM for independent samples increasing by 6.43%(from 0.6488 to0.6905).The modified model demonstrated greater accuracy in capturing disaster severity and distribution of TCs with significant speed characteristics or with regular tracks.This improvement stemmed from reduced false alarms due to the selection of analogs that are more similar to the target TC.The enhanced preassessment ability can be attributed to the key role of TC translation speed,which significantly influences TC precipitation patterns and improves TC precipitation forecasting.Since precipitation is one of the most crucial disaster-causing factors,better TC precipitation forecasting leads to improved disaster preassessment outcomes.These findings emphasize the promising potential of the DSAEF_LTD model for future TC disaster research and management,contributing to the achievement of the Sustainable Development Goals set by the United Nations 2030 Agenda by strengthening coastal resilience.
文摘This study aims to explore the impact of combined health education and dietary guidance on the speed of postoperative recovery in patients with gastrointestinal polyps.A specific number of patients who underwent gastrointestinal polyp resection were selected and randomly divided into a control group and an experimental group.The control group received routine nursing,while the experimental group implemented combined health education and dietary guidance on this basis.By comparing the recovery indicators of the two groups,it was found that the recovery speed of the experimental group was significantly faster than that of the control group,indicating that this combined intervention method can effectively promote patient recovery.
基金support from the National Natural Science Foundation of China(No.52271287)funding from the State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation,Tianjin University。
文摘During the hoisting process of the offshore substation,changes in the hoisting speed can affect the hoisting system.Therefore,this study set four different speed conditions for the lifting and lowering stages of the installation process,and studied the impact of different lifting and lowering speeds on the hoisting system under the same environmental conditions through numerical simulation.The results show that during the lifting operation,as the lifting speed increases,the swing motion of the substation and the installation vessel tends to decrease,and the faster the hoisting speed,the more obvious the swing suppression of the substation and the installation vessel,and the smaller the fluctuation in the tension amplitude of the slings and mooring lines.In contrast,during the lowering operation,as the lowering speed increases,the swing motion of the substation and the installation vessel tends to increase,and the faster the lowering speed,the more obvious the swing amplification effect of the substation and the installation vessel.Therefore,during hoisting operations,increasing the lifting speed and reducing the lowering speed can mitigate the motion performance of the hoisting coupling system,reduce the tension amplitude variation of the sling and mooring,and ensure the smooth progress of the hoisting operation.
基金supported by the National Natural Science Foundation of China(No.52171284)。
文摘Wind speed is a crucial parameter affecting wind energy utilization.However,its volatility leads to time-varying power output.Herein,a novel Seq2Seq model integrating deep learning,data denoising,and a shape-aware loss function is proposed for accurate multistep wind speed forecasting.In this model,the wind speed data is first denoised using the maximal overlap discrete wavelet transform.Next,an encoder-decoder network based on a temporal convolutional network,bidirectional gated recurrent unit,and multihead self-attention is employed for forecasting.Additionally,to enhance the ability of the model to identify temporal dynamics,a shape-aware loss function,ITILDE-Q,is employed in the model.To verify the effectiveness of the proposed model,a comparative experiment and an ablation experiment were conducted using three datasets of measured wind speeds.Three error metrics and a similarity metric were adopted for comprehensive evaluation.The experimental results showed that the proposed model consistently outperforms benchmark models in all tested forecasting scenarios,with particularly pronounced differences in performance over longer forecast horizons.Furthermore,the synergistic interaction of the three key components contributes to the extraordinary performance of the proposed model.
基金funded by Science and Technology Research and Development Program Project of China Railway Group Limited(No.2023-Major-02)National Natural Science Foundation of China(Grant No.52378200)Sichuan Science and Technology Program(Grant No.2024NSFSC0017).
文摘Accurate wind speed prediction is crucial for stabilizing power grids with high wind energy penetration.This study presents a novel machine learning model that integrates clustering,deep learning,and transfer learning to mitigate accuracy degradation in 24-h forecasting.Initially,an optimized DB-SCAN(Density-Based Spatial Clustering of Applications with Noise)algorithm clusters wind fields based on wind direction,probability density,and spectral features,enhancing physical interpretability and reducing training complexity.Subsequently,a ResNet(Residual Network)extracts multi-scale patterns from decomposed wind signals,while transfer learning adapts the backbone network across clusters,cutting training time by over 90%.Finally,a CBAM(Convolutional Block Attention Module)attention mechanism is employed to prioritize features for LSTM-based prediction.Tested on the 2015 Jena wind speed dataset,the model demonstrates superior accuracy and robustness compared to state-of-the-art baselines.Key innovations include:(a)Physics-informed clustering for interpretable wind regime classification;(b)Transfer learning with deep feature extraction,preserving accuracy while minimizing training time;and(c)On the 2016 Jena wind speed dataset,the model achieves MAPE(Mean Absolute Percentage Error)values of 16.82%and 18.02%for the Weibull-shaped and Gaussian-shaped wind speed clusters,respectively,demonstrating the model’s robust generalization capacity.This framework offers an efficient and effective solution for long-term wind forecasting.
文摘Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).
文摘The dual challenges of critical speed prediction inaccuracies and ambiguous vibration behaviors are present in high-speed flexible rotors,particularly in free turbine rotors in turboshaft engine systems.The study begins with an examination of the rotor-bearing bidirectional coupling mechanism,with a primary focus on the nonlinear characteristics of the bearing.An investigation is carried out on the mechanical modeling methodologies for four-point contact ball bearings(FPCBBs)and cylindrical roller bearings(CRBs).To address the issue of excessive computational time in traditional bearing calculation methods,the sled dog optimization(SDO)algorithm is substituted for the conventional Newton-Raphson method.A rotor-bearing coupling dynamics model is developed by the finite element and lumped mass methods,with experimental validation achieved through a simulator test rig.The effects of three internal bearing parameters in FPCBBs(arching width and raceway groove curvature coefficient)and CRBs(initial radial clearance)on the critical speed characteristics and vibrational behavior of rotorbearing coupled systems are examined.The numerical simulation results show some interesting conclusions.
基金supported by the National Natural Science Foundation of China(No.52175214)。
文摘In this paper,a novel guidance law is proposed which can achieve the desired impact speed and angle simultaneously for unpowered gliding vehicles.A guidance law with only impact angle constraint is used to produce the guidance profile,and its convergence in the varying speed scenario is proved.A relationship between flight states,guidance input and impact speed is established.By applying the fixed-time convergence control theory of error dynamics,an impact speed corrector is built with the above guidance profile,which can implement impact speed correction without affecting the impact angle constraint.Numerical simulations with various impact speed and angle constraints are conducted to demonstrate the performance of the proposed guidance law,and the robustness is also verified by Monte Carlo tests.
基金supported by Technology Innovation Fund of China Coal Research Institute(2022CX-I-04)Science and Technology Innovation Venture Capital Project of China Coal Technology Engineering Group(2020-2-TD-CXY005)。
文摘Enhancing the mining speed of a working face has become the primary approach to achieve high production and efficiency in coal mines,thereby further improving the production capacity.However,the problem of rock bursts resulting from this approach has become increasingly serious.Therefore,to implement coal mine safety and efficient extraction,the impact of deformation pressure caused by different mining speeds should be considered,and a reasonable mining speed of the working face should be determined.The influence of mining speed on overlying rock breaking in the stope is analyzed by establishing a key layer block rotation and subsidence model.Results show that with the increasing mining speed,the compression amount of gangue in the goaf decreases,and the rotation and subsidence amount of rock block B above goaf decreases,forcing the rotation and subsidence amount of rock block A above roadway to increase.Consequently,the contact mode between rock block A and rock block B changes from line contact to point contact,and the horizontal thrust and shear force between blocks increase.The increase in rotation and subsidence of rock block A intensifies the compression degree of coal and rock mass below the key layer,thereby increasing the stress concentration degree of coal and rock mass as well as the total energy accumulation.In addition,due to the insufficient compression of gangue in the goaf,the bending and subsidence space of the far-field key layer are limited,the length of the suspended roof increases,and the influence range of mining stress and the energy accumulation range expand.Numerical test results and underground microseismic monitoring results verify the correlation between mining speed and stope energy,and high-energy events generally appear 1-2 d after the change in mining speed.On this basis,the statistical principle confirms that the maximum mining speed of the working face at 6 m/d is reasonable.
基金supported by the National Natural Science Foundation of China(52174109)Program for Innovative Research Team(in Science and Technology)in University of Henan Province(22IRTSTHN005)+1 种基金Key Research and Development Project of Henan Province(242102240029)Key Research Project of Institutions of Higher Education in Henan Province(24A580001).
文摘To reveal the rock burst mechanism,the stress and failure characteristics of coal-rock strata under different advancing speeds of mining working face were explored by theoretical analysis,simulation,and engineering monitoring.The relationship between energy accumulation and release was analyzed,and a reasonable mining speed according to specific projects was recommended.The theoretical analysis shows that as the mining speed increases from 4 to 15 m/d,the rheological coefficient of coal mass ranges from 0.9 to 0.4,and the elastic energy of coal mass accumulation varies from 100 to 900 kJ.Based on the simulation,there is a critical advancing speed,the iteration numbers of simulation are less than 15,000 per mining 10 m coal seam,the overburden structure is obvious,the abutment pressure in coal mass is large,and the accumulated energy is large,which is easy to cause strong rock burst.When the iteration number is greater than 15,000,the static force of coal mass increases slightly,but there is no obvious rock burst.Based on engineering monitoring,the mining speed of a mine is less than 8 m/d,and the periodic weighting distance is about 17 m;as the mining speed is greater than 10 m/d,and the periodic weighting distance is greater than 20 m;as the mining speed is 3-8 m/d,and the range of high stress in surrounding rock is 48 m;as the advancing speed is 8-12 m/d,and the high-stress range in surrounding rock is 80 m.Moreover,as the mining speed is less than 8 cut cycles,the micro seismic energy is less than 10,000 J;as the mining speed is 12 cut cycles,the microseismic energy is about 20,000 J.In summary,the advancing speed is positively correlated with the micro seismic event;as the mining speed increases,the accumulated elastic energy of surrounding rock is greater,which is easy to cause rock burst.The comprehensive analysis indicates the daily advance speed of the mine is not more than 12 cut cycles.
基金supported in part by the Universitat Politècnica de València under grant PAID-10-21supported through AMRITA Seed Grant(Proposal ID:ASG2022188)。
文摘Switched Reluctance Motors(SRMs),outfitted with rugged construction,good speed range,high torque density,and rare earth-free nature that outweigh induction motors(IM)and permanent magnet synchronous motor(PMSM),afford a broad range of applications in the domain of electric vehicles(EVs).Standard copper magnetic wire and low-carbon steel laminations are used to construct SRMs,which give them high efficiency in the range of 85-95%.Despite SRM's desirable features over traditional motor-speed drives,high torque ripples and radial distortions constrain their deployment in EVs.Precise rotor position is imperative for effective management of the speed and torque of SRMs.This paper provides an illustrative compendium on review of the torque-speed control and ripple mitigation techniques using design enhancements and control methods for SRM drives for EV applications.The various schemes were evaluated on their performance metricsoperational speed range,control complexity,practical realization,need for pre-stored parameters(look-up tables of current,inductance and torque profiles)and motor controller memory requirements.The findings provide valuable insights into balancing the gains and trade-offs associated with EV applications.Furthermore,they pinpoint opportunities for enhancement by analyzing the cost and technical aspects of different SRM controllers.
基金Supported by the National Natural Science Foundation of China(12071162)the Natural Science Foundation of Fujian Province(2021J01302)the Fundamental Research Funds for the Central Universities(ZQN-802)。
文摘This paper deals with the monotonicity of limit wave speed c0(h)to a perturbed g KdV equation.We show the decrease of c0(h)by combining the analytic method and the numerical technique.Our results solve a special case of the open question presented by Yan et al.,and the method potentially provides a way to study the monotonicity of c0(h)for general m∈N^(+).
基金supported by the National Key Research and Development Program of China(2022YFA1404400)the National Natural Science Foundation of China(62122072,12174368,61705216,62405306)+4 种基金Anhui Provincial Department of Science and Technology(202203a07020020,18030801138)Anhui Provincial Natural Science Foundation(2308085QA21,2408085QF187)the USTC Research Funds of the Double First-Class Initiative(YD2090002015)the Institute of Artificial Intelligence at Hefei Comprehensive National Science Center(23YGXT005)the Fundamental Research Funds for the Central Universities(WK2090000083).
文摘Ultrasound computed tomography(USCT)is a noninvasive biomedical imaging modality that offers insights into acoustic properties such as the sound speed(SS)and acoustic attenuation(AA)of the human body,enhancing diagnostic accuracy and therapy planning.Full waveform inversion(FWI)is a promising USCT image reconstruction method that optimizes the parameter fields of a wave propagation model via gradient-based optimization.However,twodimensional FWI methods are limited by their inability to account for three-dimensional wave propagation in the elevation direction,resulting in image artifacts.To address this problem,we propose a three-dimensional time-domain full waveform inversion algorithm to reconstruct the SS and AA distributions on the basis of a fractional Laplacian wave equation,adjoint field formulation,and gradient descent optimization.Validated by two sets of simulations,the proposed algorithm has potential for generating high-resolution and quantitative SS and AA distributions.This approach holds promise for clinical USCT applications,assisting early disease detection,precise abnormality localization,and optimized treatment planning,thus contributing to better healthcare outcomes.
文摘Application of variable speed limits(VSL)is gradually increasingly implemented especially on highways.As a result of conducted studies and implementations,it is observed that the variable speed limits have reduced the number of car accidents as well as proved positive results in terms of delays and environmental factors.Purpose of this study is to develop an algorithm for VSL application that is considered to be applied on Istanbul D100 highway and to assess the effects of application.Algorithm that is developed for VSL is a different VSL algorithm and compared with the constant speed system.According to obtained results,when the proposed system is compared to current system,it is observed that the number of delays and average stops are reduced%30 and%40 respectively and also emissions reduced at the rate of%12.
基金Supported by the Major Science and Technology Projects in Jilin Province and Changchun City(20220301010GX).
文摘When the proton exchange membrane fuel cell(PEMFC)system is running,there will be a condition that does not require power output for a short time.In order to achieve zero power output under low power consumption,it is necessary to consider the diversity of control targets and the complexity of dynamic models,which brings the challenge of high-precision tracking control of the stack output power and cathode intake flow.For system idle speed control,a modelbased nonlinear control framework is constructed in this paper.Firstly,the nonlinear dynamic model of output power and cathode intake flow is derived.Secondly,a control scheme combining nonlinear extended Kalman filter observer and state feedback controller is designed.Finally,the control scheme is verified on the PEMFC experimental platform and compared with the proportion-integration-differentiation(PID)controller.The experimental results show that the control strategy proposed in this paper can realize the idle speed control of the fuel cell system and achieve the purpose of zero power output.Compared with PID controller,it has faster response speed and better system dynamics.
基金supported by the EU H2020 Research and Innovation Program under the Marie Sklodowska-Curie Grant Agreement(Project-DEEP,Grant No.101109045)the National Natural Science Foundation of China(No.NSFC 61925105 and 62171257)the Tsinghua University-China Mobile Communications Group Co.,Ltd.Joint Institute,and the Fundamental Research Funds for the Central Universities,China(No.FRF-NP-20-03).
文摘This paper explores the development of interpretable data elements from raw data using Kolmogorov-Arnold Networks(KAN).With the exponential growth of data in contemporary society,there is an urgent need for effective data processing methods to unlock the full potential of this resource.The study focuses on the application of KAN in the transportation sector to transform raw traffic data into meaningful data elements.The core of the research is the KANT-GCN model,which synergizes Kolmogorov-Arnold Networks with Temporal Graph Convolutional Networks(T-GCN).This innovative model demonstrates superior performance in predicting traffic speeds,outperforming existing methods in terms of accuracy,reliability,and interpretability.The model was evaluated using real-world datasets from Shenzhen,Los Angeles,and the San Francisco Bay Area,showing significant improvements in different metrics.The paper highlights the potential of KAN-T-GCN to revolutionize data-driven decision-making in traffic management and other sectors,underscoring its ability to handle dynamic updates and maintain data integrity.
基金supported by the National Natural Science Foundation(No.42176020)the Open Research Fund of State Key Laboratory of Target Vulnerability Assessment(No.YSX2024KFYS001)+1 种基金the National Key Research and Development Program(No.2022YFC3105002)the Project from Key Laboratory of Marine Environmental Information Technology(No.2023GFW-1047).
文摘Sea-surface wind is a vital meteorological element in marine activities and climate research.This study proposed the spectral attention enhanced multidimensional feature fusion convolutional long short-term memory(LSTM)network(SAMFF-Conv-LSTM),a novel approach for sea-surface wind-speed prediction that emphasizes the temporal characteristics of data samples.The model incorporates the Fourier transform to extract time-and frequency-domain features from wave and wind variables.For the 12 h prediction,the SAMFF-ConvLSTM achieved a correlation coefficient of 0.960 and a root mean square error(RMSE)of 1.350 m/s,implying a high prediction accuracy.For the 24 h prediction,the RMSE of the SAMFF-ConvLSTM was reduced by 38.11%,14.26%,and 13.36%compared with those of the convolutional neural network,gated recurrent units,and convolutional LSTM(ConvLSTM),respectively.These results confirm the superior reliability and accuracy of the SAMFF-ConvLSTM over traditional models in theoretical and practical applications.
基金supported by the Natural Science Basic Research Program of Shanxi(Grant No.2024JC-YBMS-025)the Innovation Capability Support Program of Shanxi(Grant No.2024RS-CXTD-88)。
文摘This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward spreading speeds for the infective individuals, which can be used to estimate how fast the disease spreads. To overcome the difficulty arising from the lack of comparison principle for such time-space periodic nonmonotone systems, our proof is mainly based on constructing a series of scalar time-space periodic equations, establishing the spreading speeds for such auxiliary equations and using comparison methods. It may be the first work to study the spreading speed for time-space periodic non-monotone systems.
基金the support from the National Natural Science Foundation of China (Grant No. 42175070)supported by the National Natural Science Foundation of China (Grant No. 42288101)supported by the National Key Scientific and Technological Infrastructure project “Earth System Numerical Simulation Facility” (Earth Lab)。
文摘By applying the convolution-based Hilbert transform in the zonal direction on six-hourly streamfunction fields at200 h Pa, we present the climatology and trends of the local wave period, and zonal and meridional phase speeds, of Rossby waves over the globe during the solstice seasons of 1979–2023. While partly similar to and inspired by Fragkoulidis and Wirth(2020), our method differs in its ability to cover both planetary-scale and synoptic-scale waves over not only the extratropics, but also the tropics and subtropics. Based on a physically reasonable global distribution of wave periods, our key new finding is a robust prolonging of wave periods over most regions of the tropics and subtropics during both solstice seasons of 1979–2023, except for the tropical Atlantic, which experiences a shortened wave period during June–July–August of 1979–2022. Both the prolonging and shortening of wave periods are mainly associated with the changes in planetary-scale waves. Regionally varying trends of the zonal phase speed(Cpx) of synoptic waves are consistent in sign with, but smaller in magnitude than, the trends of local zonal wind, confirming the conclusion of Wu and Lu(2023)on the opposite effects of zonal wind and the meridional gradient of potential vorticity on Cpx. Meanwhile, the Cpx trends of planetary-scale waves are relatively weak, and do not exhibit a robust relation with the trend of zonal wind. These new results are helpful toward better understanding the changes in atmospheric waves and extreme events under global warming.
