Based on the AfKdV equation of Xu et al.([1]), a theory on the velocities of the precursor soliton generation in two-layer flow over topography is presented in the present paper. Moving velocities of precursor soliton...Based on the AfKdV equation of Xu et al.([1]), a theory on the velocities of the precursor soliton generation in two-layer flow over topography is presented in the present paper. Moving velocities of precursor solitons, of the first zero-crossing of the tailing wavetrain and of the flow behind the topography are found theoretically. It is shown that for a given topography, when its moving velocities are at the resonant points, we have the following rules: the ratio of the moving velocity of the precursor solitons to that of the first zero-crossing of the tailing wavetrain equals -4/3. At the same time, the ratio of the width of generating region of the precursor solitons to that of the depressed water region equals also -4/3. The theoretical results are examined by means of numerical calculation. The comparison between the theoretical and numerical results are found in good agreement. For different stratified parameters of two-layer how, the velocities of the precursor soliton generation are also predicted in terms of the present theoretical results.展开更多
A theory of tailing wavetrain generation for the precursor soliton generation in two-layer flow is presented by using averaged KdV equations (AKdV), which are derived by the authors in terms of Whitham's method of...A theory of tailing wavetrain generation for the precursor soliton generation in two-layer flow is presented by using averaged KdV equations (AKdV), which are derived by the authors in terms of Whitham's method of averaging([1,2]). From the AKdV equations, group velocities of the tailing wavetrain generation are obtained by means of generating conditions of the tailing wavetrains, furthermore an analytical solution of the tailing wavetrain generation is found theoretically. A comparison between the theoretical and numerical results is carried out in the present paper, which shows that the theoretical results are in good agreement with the numerical ones, obtained from the fKdV equation in two-layer flow with the depth of unity in the rest.展开更多
Hydraulic falls and asymptotic mean levels of two-layer flow are determined by means of AfKdV equation in phase coordinate theoretically. By present theory, the hydraulic falls Hf depend on a characteristic value of t...Hydraulic falls and asymptotic mean levels of two-layer flow are determined by means of AfKdV equation in phase coordinate theoretically. By present theory, the hydraulic falls Hf depend on a characteristic value of the MfKdV equation at the subcritical cutoff points It is proved that the differences of the asymptotic mean levels upstream and downstream at the subcritical cutoff points are equal to 2 A relation between and the asymptotic mean levels at the subcritical cutoff points is also found in terms of the solution of the hydraulic falls. Because the AfKdV equation is derived based on the small topography assumption, for semicircular topography the valid region of this theory is α< 0. 35, in which α is radius of the semicircular topography. An experiment is carried out to examine the theory of the present paper. From comparisons between the theoretical and experimental results. it is shown that they are in better agreement. Under conditions of different stratified parameters, the hydraulic falls of two-layer flow are predicted theoretically. This work was supered by the Foundation of the State Education COmmission 'The dynamics of upper ocean'.展开更多
Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered so...Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.展开更多
The problem of oblique wave （internal wave） propagation over a small deformation in a channel flow consisting of two layers was considered. The upper fluid was assumed to be bounded above by a rigid lid, which is an...The problem of oblique wave （internal wave） propagation over a small deformation in a channel flow consisting of two layers was considered. The upper fluid was assumed to be bounded above by a rigid lid, which is an approximation for the free surface, and the lower one was bounded below by an impermeable bottom surface having a small deformation; the channel was unbounded in the horizontal directions. Assuming irrotational motion, the perturbation technique was employed to calculate the first-order corrections of the velocity potential in the two fluids by using Green＇s integral theorem suitably with the introduction of appropriate Green＇s functions. Those functions help in calculating the reflection and transmission coefficients in terms of integrals involving the shape ftmction c（x） representing the bottom deformation. Three-dimensional linear water wave theory was utilized for formulating the relevant boundary value problem. Two special examples of bottom deformation were considered to validate the results. Consideration of a patch of sinusoidal ripples （having the same wave number） shows that the reflection coefficient is an oscillatory function of the ratio of twice the x-component of the wave number to the ripple wave number. When this ratio approaches one, the theory predicts a resonant interaction between the bed and the interface, and the reflection coefficient becomes a multiple of the number of ripples. High reflection of incident wave energy occurs if this number is large. Similar results were observed for a patch of sinusoidal ripples having different wave numbers. It was also observed that for small angles of incidence, the reflected energy is greater compared to other angles of incidence up to π/ 4. These theoretical observations are supported by graphical results.展开更多
This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerge...This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.展开更多
Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class at...Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.展开更多
In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapi...In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.展开更多
BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To ...BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.展开更多
This paper reports that an experimental study is conducted to examine the dynamics of the outflow in two-layer exchange flows in a channel connecting between two water bodies with a small density difference. The exper...This paper reports that an experimental study is conducted to examine the dynamics of the outflow in two-layer exchange flows in a channel connecting between two water bodies with a small density difference. The experiments reveal the generation of Kelvin-Helmholtz (KH) instabilities within the hydraulically sub-critical flow region of the channel. During maximal exchange, those KH instabilities develops into large-amplitude KH waves as they escape the channel exit into the reservoir. The propagation speed of those waves, their generation frequency and their amplitudes are studied. The dynamics of the outflow and these waves are directly linked to the hydraulic conditions of the exchange flow within the channel.展开更多
Photothermal synergistic catalytic systems for treating volatile organic compounds(VOCs)have attracted signif-icant attention due to their energy efficiency and potential to reduce carbon emissions.However,the mechani...Photothermal synergistic catalytic systems for treating volatile organic compounds(VOCs)have attracted signif-icant attention due to their energy efficiency and potential to reduce carbon emissions.However,the mechanism underlying the synergistic reaction remains a critical issue.This study introduces a photothermal synergistic system for the removal of ethyl acetate(EA)by synthesizing Cu-doped OMS-2(denoted as Cu-OMS-2).Under ultraviolet-visible(UV–Vis)irradiation in a flow system,the Cu-OMS-2 catalyst exhibited significantly enhanced performance in the EA degradation process,nearly doubling the effectiveness of pure OMS-2,and increasing carbon dioxide yield by 20%.This exceptional performance is attributed to the synergistic effect of increased oxygen vacancies(OV)at OMS-2 active sites and Cu doping,as confirmed by H2-TPR,O_(2)-TPD,and CO consump-tion measurements.This study clarifies the catalytic mechanism of light-assisted thermocatalysis and offers a novel strategy for designing photothermal catalysts with homogeneous Cu-doped nanorods for VOC removal.展开更多
Vortex-induced vibration(VIV)of an underwater manipulator in pulsating flow presents a notable engineering problem in precise control due to the velocity variation in the flow.This study investigates the VIV response ...Vortex-induced vibration(VIV)of an underwater manipulator in pulsating flow presents a notable engineering problem in precise control due to the velocity variation in the flow.This study investigates the VIV response of an underwater manipulator subjected to pulsating flow,focusing on how different postures affect the behavior of the system.The effects of pulsating parameters and manipulator arrangement on the hydrodynamic coefficient,vibration response,motion trajectory,and vortex shedding behaviors were analyzed.Results indicated that the cross flow vibration displacement in pulsating flow increased by 32.14%compared to uniform flow,inducing a shift in the motion trajectory from a crescent shape to a sideward vase shape.In the absence of interference between the upper and lower arms,the lift coefficient of the manipulator substantially increased with rising pulsating frequency,reaching a maximum increment of 67.0%.This increase in the lift coefficient led to a 67.05%rise in the vibration frequency of the manipulator in the in-line direction.As the pulsating amplitude increased,the drag coefficient of the underwater manipulator rose by 36.79%,but the vibration frequency in the cross-flow direction decreased by 56.26%.Additionally,when the upper and lower arms remained in a state of mutual interference,the cross-flow vibration amplitudes of the upper and lower arms were approximately 1.84 and 4.82 times higher in a circular-elliptical arrangement compared to an elliptical-circular arrangement,respectively.Consequently,the flow field shifted from a P+S pattern to a disordered pattern,disrupting the regularity of the motion trajectory.展开更多
Debris flow events are frequent in Tajikistan,yet comprehensive investigations at the regional scale are limited.This study integrates remote sensing,Geographic Information System,and machine learning techniques to ev...Debris flow events are frequent in Tajikistan,yet comprehensive investigations at the regional scale are limited.This study integrates remote sensing,Geographic Information System,and machine learning techniques to evaluate debris flow susceptibility and associated hazards across Tajikistan.A dataset comprising 405 documented debris flow points and 14 influencing factors,encompassing geological,climatic-hydrological,and anthropogenic variables,was established.Three machine learning algorithms—Random Forest,Support Vector Machine(SVM),and Multi-layer Perceptron—were applied to generate susceptibility maps and delineate debris flow risk zones.The results indicate that the areas of higher and high susceptibility accounted for 20.43%and 4.41%of the national area,respectively,and were predominantly concentrated along the Zeravshan and Vakhsh river basins.Among the evaluated models,SVM model demonstrated the highest predictive performance.Beyond conventional topographic and environmental controls,drought conditions were identified as a critical factor influencing debris flow occurrence within the arid and semi-arid mountainous regions of Tajikistan.These findings provide a scientific basis for regional debris flow risk management and disaster mitigation planning,and offer practical guidance for selecting conditioning factors in machine-learning-based susceptibility assessments in other dry mountainous environments.展开更多
Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate ...Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate this challenge,we present an enhanced semi-supervised learning approach based on the Mean Teacher framework,incorporating a novel feature loss module to maximize classification performance with limited labeled samples.The model studies show that the proposed model surpasses both the baseline Mean Teacher model and fully supervised method in accuracy.Specifically,for datasets with 20%,30%,and 40%label ratios,using a single training iteration,the model yields accuracies of 78.61%,82.21%,and 85.2%,respectively,while multiple-cycle training iterations achieves 82.09%,81.97%,and 81.59%,respectively.Furthermore,scenario-specific training schemes are introduced to support diverse deployment need.These findings highlight the potential of the proposed technique in minimizing labeling requirements and advancing intelligent blast furnace diagnostics.展开更多
Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating In...Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.展开更多
To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hyb...To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.展开更多
Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose...Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose a joint gravity and magnetic inversion methodfor two-layer models by concentrating on the relationship between the change of thicknessI and position of the middle layer and anomaly and discuss the effects of the key parameters. Model tests and application to field data show the validity of this method.展开更多
A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an i...A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an infinite matrix.The interations of the reinforced phases are taken into account by using the average matrix stress concept.When the external layer vanishes,the proposed model reduces to the classical Mori-Tanaka's model for spherical inclusions.Theoretical results for the composite of polyester matrix filled by hollow glass spheres and voids show excellent agreement with experimental results.展开更多
Many rock avalanches were triggered by the Wenchuan earthquake on May 12, 2008 in southwest China. Protection galleries covered with a single soil layer are usually used to protect against rockfall. Since one-layer pr...Many rock avalanches were triggered by the Wenchuan earthquake on May 12, 2008 in southwest China. Protection galleries covered with a single soil layer are usually used to protect against rockfall. Since one-layer protection galleries do not have sufficient buffer capacity, a two-layered absorbing system has been designed. This study aims to find whether an expanded poly-styrol （EPS） cushion, which is used in the soil-covered protection galleries for shock absorption, could be positioned under dynamic loadings. The dynamic impacts of the two-layered absorbing system under the conditions of rock avalanches are numerically simulated through a 2D discrete dement method. By selecting reasonable parameters, a series of numerical experiments were conducted to find the best combination for the two- layered absorbing system. The values of the EPS layer area as a percentage of the total area were set as 0% （Sl）, 22~ （S2）, and 70% （$3）. 22~ of the area of the EPS layer was found to be a reasonable value, and experiments were conducted to find the best position of the EPS layer in the two-layered absorbing system. The numerical results yield useful conclusions regarding the interaction between the impacting avalanches and the two-layered absorbing system. The soil layer can absorb the shock energy effectively and S2 （0.4-m thick EPS cushion covered with soil layer） is the most efficient combination, which can reduce the impact force, compared with the other combinations.展开更多
基金The project supported by the National Natural Science Foundation of China under the Grant No.49776284
文摘Based on the AfKdV equation of Xu et al.([1]), a theory on the velocities of the precursor soliton generation in two-layer flow over topography is presented in the present paper. Moving velocities of precursor solitons, of the first zero-crossing of the tailing wavetrain and of the flow behind the topography are found theoretically. It is shown that for a given topography, when its moving velocities are at the resonant points, we have the following rules: the ratio of the moving velocity of the precursor solitons to that of the first zero-crossing of the tailing wavetrain equals -4/3. At the same time, the ratio of the width of generating region of the precursor solitons to that of the depressed water region equals also -4/3. The theoretical results are examined by means of numerical calculation. The comparison between the theoretical and numerical results are found in good agreement. For different stratified parameters of two-layer how, the velocities of the precursor soliton generation are also predicted in terms of the present theoretical results.
基金The project is supported by the National Natural Science Foundation of China(No.49776284)
文摘A theory of tailing wavetrain generation for the precursor soliton generation in two-layer flow is presented by using averaged KdV equations (AKdV), which are derived by the authors in terms of Whitham's method of averaging([1,2]). From the AKdV equations, group velocities of the tailing wavetrain generation are obtained by means of generating conditions of the tailing wavetrains, furthermore an analytical solution of the tailing wavetrain generation is found theoretically. A comparison between the theoretical and numerical results is carried out in the present paper, which shows that the theoretical results are in good agreement with the numerical ones, obtained from the fKdV equation in two-layer flow with the depth of unity in the rest.
文摘Hydraulic falls and asymptotic mean levels of two-layer flow are determined by means of AfKdV equation in phase coordinate theoretically. By present theory, the hydraulic falls Hf depend on a characteristic value of the MfKdV equation at the subcritical cutoff points It is proved that the differences of the asymptotic mean levels upstream and downstream at the subcritical cutoff points are equal to 2 A relation between and the asymptotic mean levels at the subcritical cutoff points is also found in terms of the solution of the hydraulic falls. Because the AfKdV equation is derived based on the small topography assumption, for semicircular topography the valid region of this theory is α< 0. 35, in which α is radius of the semicircular topography. An experiment is carried out to examine the theory of the present paper. From comparisons between the theoretical and experimental results. it is shown that they are in better agreement. Under conditions of different stratified parameters, the hydraulic falls of two-layer flow are predicted theoretically. This work was supered by the Foundation of the State Education COmmission 'The dynamics of upper ocean'.
文摘Open caissons are widely used in foundation engineering because of their load-bearing efficiency and adaptability in diverse soil conditions.However,accurately predicting their undrained bearing capacity in layered soils remains a complex challenge.This study presents a novel application of five ensemble machine(ML)algorithms-random forest(RF),gradient boosting machine(GBM),extreme gradient boosting(XGBoost),adaptive boosting(AdaBoost),and categorical boosting(CatBoost)-to predict the undrained bearing capacity factor(Nc)of circular open caissons embedded in two-layered clay on the basis of results from finite element limit analysis(FELA).The input dataset consists of 1188 numerical simulations using the Tresca failure criterion,varying in geometrical and soil parameters.The FELA was performed via OptumG2 software with adaptive meshing techniques and verified against existing benchmark studies.The ML models were trained on 70% of the dataset and tested on the remaining 30%.Their performance was evaluated using six statistical metrics:coefficient of determination(R²),mean absolute error(MAE),root mean squared error(RMSE),index of scatter(IOS),RMSE-to-standard deviation ratio(RSR),and variance explained factor(VAF).The results indicate that all the models achieved high accuracy,with R²values exceeding 97.6%and RMSE values below 0.02.Among them,AdaBoost and CatBoost consistently outperformed the other methods across both the training and testing datasets,demonstrating superior generalizability and robustness.The proposed ML framework offers an efficient,accurate,and data-driven alternative to traditional methods for estimating caisson capacity in stratified soils.This approach can aid in reducing computational costs while improving reliability in the early stages of foundation design.
文摘The problem of oblique wave （internal wave） propagation over a small deformation in a channel flow consisting of two layers was considered. The upper fluid was assumed to be bounded above by a rigid lid, which is an approximation for the free surface, and the lower one was bounded below by an impermeable bottom surface having a small deformation; the channel was unbounded in the horizontal directions. Assuming irrotational motion, the perturbation technique was employed to calculate the first-order corrections of the velocity potential in the two fluids by using Green＇s integral theorem suitably with the introduction of appropriate Green＇s functions. Those functions help in calculating the reflection and transmission coefficients in terms of integrals involving the shape ftmction c（x） representing the bottom deformation. Three-dimensional linear water wave theory was utilized for formulating the relevant boundary value problem. Two special examples of bottom deformation were considered to validate the results. Consideration of a patch of sinusoidal ripples （having the same wave number） shows that the reflection coefficient is an oscillatory function of the ratio of twice the x-component of the wave number to the ripple wave number. When this ratio approaches one, the theory predicts a resonant interaction between the bed and the interface, and the reflection coefficient becomes a multiple of the number of ripples. High reflection of incident wave energy occurs if this number is large. Similar results were observed for a patch of sinusoidal ripples having different wave numbers. It was also observed that for small angles of incidence, the reflected energy is greater compared to other angles of incidence up to π/ 4. These theoretical observations are supported by graphical results.
基金supported by MHRD as researcher C.K.Neog received the MHRD Institute GATE scholarship from Govt.of India.
文摘This study investigates the effects of radiation force due to the rotational pitch motion of a wave energy device,which comprises a coaxial bottom-mounted cylindrical caisson in a two-layer fluid,along with a submerged cylindrical buoy.The system is modeled as a two-layer fluid with infinite horizontal extent and finite depth.The radiation problem is analyzed in the context of linear water waves.The fluid domain is divided into outer and inner zones,and mathematical solutions for the pitch radiating potential are derived for the corresponding boundary valve problem in these zones using the separation of variables approach.Using the matching eigenfunction expansion method,the unknown coefficients in the analytical expression of the radiation potentials are evaluated.The resulting radiation potential is then used to compute the added mass and damping coefficients.Several numerical results for the added mass and damping coefficients are investigated for numerous parameters,particularly the effects of the cylinder radius,the draft of the submerged cylinder,and the density proportion between the two fluid layers across different frequency ranges.The major findings are presented and discussed.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(IITP)—Innovative Human Resource Development for Local Intellectualization program grant funded by the Korea government(MSIT)(IITP-2025-RS-2022-00156334)in part by Liaoning Province Nature Fund Project(2024-BSLH-214).
文摘Network Intrusion Detection System(NIDS)detection of minority class attacks is always a difficult task when dealing with attacks in complex network environments.To improve the detection capability of minority-class attacks,this study proposes an intrusion detection method based on a two-layer structure.The first layer employs a CNN-BiLSTM model incorporating an attention mechanism to classify network traffic into normal traffic,majority class attacks,and merged minority class attacks.The second layer further segments the minority class attacks through Stacking ensemble learning.The datasets are selected from the generic network dataset CIC-IDS2017,NSL-KDD,and the industrial network dataset Mississippi Gas Pipeline dataset to enhance the generalization and practical applicability of the model.Experimental results show that the proposed model achieves an overall detection accuracy of 99%,99%,and 95%on the CIC-IDS2017,NSL-KDD,and industrial network datasets,respectively.It also significantly outperforms traditional methods in terms of detection accuracy and recall rate for minority class attacks.Compared with the single-layer deep learning model,the two-layer structure effectively reduces the false alarm rate while improving the minority-class attack detection performance.The research in this paper not only improves the adaptability of NIDS to complex network environments but also provides a new solution for minority-class attack detection in industrial network security.
基金supported by the Basic Scientific Research Business Fund Project of Higher Education Institutions in Heilongjiang Province(145409601)the First Batch of Experimental Teaching and Teaching Laboratory Construction Research Projects in Heilongjiang Province(SJGZ20240038).
文摘In the wake of major natural disasters or human-made disasters,the communication infrastruc-ture within disaster-stricken areas is frequently dam-aged.Unmanned aerial vehicles(UAVs),thanks to their merits such as rapid deployment and high mobil-ity,are commonly regarded as an ideal option for con-structing temporary communication networks.Con-sidering the limited computing capability and battery power of UAVs,this paper proposes a two-layer UAV cooperative computing offloading strategy for emer-gency disaster relief scenarios.The multi-agent twin delayed deep deterministic policy gradient(MATD3)algorithm integrated with prioritized experience replay(PER)is utilized to jointly optimize the scheduling strategies of UAVs,task offloading ratios,and their mobility,aiming to diminish the energy consumption and delay of the system to the minimum.In order to address the aforementioned non-convex optimiza-tion issue,a Markov decision process(MDP)has been established.The results of simulation experiments demonstrate that,compared with the other four base-line algorithms,the algorithm introduced in this paper exhibits better convergence performance,verifying its feasibility and efficacy.
基金Supported by Talent Scientific Research Start-up Foundation of Wannan Medical College,No.WYRCQD2023045.
文摘BACKGROUND The early diagnosis rate of pancreatic ductal adenocarcinoma(PDAC)is low and the prognosis is poor.It is important to develop an interpretable noninvasive early diagnostic model in clinical practice.AIM To develop an interpretable noninvasive early diagnostic model for PDAC using plasma extracellular vesicle long RNA(EvlRNA).METHODS The diagnostic model was constructed based on plasma EvlRNA data.During the process of establishing the model,EvlRNA-index was introduced,and four algorithms were adopted to calculate EvlRNA-index.After the model was successfully constructed,performance evaluation was conducted.A series of bioinformatics methods were adopted to explore the potential mechanism of EvlRNA-index as the input feature of the model.And the relationship between key characteristics and PDAC were explored at the single-cell level.RESULTS A novel interpretable machine learning framework was developed based on plasma EvlRNA.In this framework,a two-layer classifier was established.A new concept was proposed:EvlRNA-index.Based on EvlRNA-index,a cancer diagnostic model was established,and a good diagnostic effect was achieved.The accuracy of PDACandCPvsHealth-Probabilistic PCA Index-SVM(PDAC and chronic pancreatitis vs health-probabilistic principal component analysis index-support vector machine)(1-18)was 91.51%,with Mathew’s correlation coefficient 0.7760 and area under the curve 0.9560.In the second layer of the model,the accuracy of PDACvsCP-Probabilistic PCA Index-RF(PDAC vs chronic pancreatitis-probabilistic principal component analysis index-random forest)(2-17)was 93.83%,with Mathew’s correlation coefficient 0.8422 and area under the curve 0.9698.Forty-nine PDAC-related genes were identified,among which 16 were known,inferring that the remaining ones were also PDAC-related genes.CONCLUSION An interpretable two-layer machine learning framework was proposed for early diagnosis and prediction of PDAC based on plasma EvlRNA,providing new insights into the clinical value of EvlRNA.
文摘This paper reports that an experimental study is conducted to examine the dynamics of the outflow in two-layer exchange flows in a channel connecting between two water bodies with a small density difference. The experiments reveal the generation of Kelvin-Helmholtz (KH) instabilities within the hydraulically sub-critical flow region of the channel. During maximal exchange, those KH instabilities develops into large-amplitude KH waves as they escape the channel exit into the reservoir. The propagation speed of those waves, their generation frequency and their amplitudes are studied. The dynamics of the outflow and these waves are directly linked to the hydraulic conditions of the exchange flow within the channel.
基金supported by the Qilu University of Technology(Shandong Academy of Sciences),the Basic Research Project of Science,Education and Industry Integration Pilot Project(No.2022PY047).
文摘Photothermal synergistic catalytic systems for treating volatile organic compounds(VOCs)have attracted signif-icant attention due to their energy efficiency and potential to reduce carbon emissions.However,the mechanism underlying the synergistic reaction remains a critical issue.This study introduces a photothermal synergistic system for the removal of ethyl acetate(EA)by synthesizing Cu-doped OMS-2(denoted as Cu-OMS-2).Under ultraviolet-visible(UV–Vis)irradiation in a flow system,the Cu-OMS-2 catalyst exhibited significantly enhanced performance in the EA degradation process,nearly doubling the effectiveness of pure OMS-2,and increasing carbon dioxide yield by 20%.This exceptional performance is attributed to the synergistic effect of increased oxygen vacancies(OV)at OMS-2 active sites and Cu doping,as confirmed by H2-TPR,O_(2)-TPD,and CO consump-tion measurements.This study clarifies the catalytic mechanism of light-assisted thermocatalysis and offers a novel strategy for designing photothermal catalysts with homogeneous Cu-doped nanorods for VOC removal.
基金Supported by the National Natural Science Foundation of China(No.51905211)A Project of the“20 Regulations for New Universities”Funding Program of Jinan(No.202228116).
文摘Vortex-induced vibration(VIV)of an underwater manipulator in pulsating flow presents a notable engineering problem in precise control due to the velocity variation in the flow.This study investigates the VIV response of an underwater manipulator subjected to pulsating flow,focusing on how different postures affect the behavior of the system.The effects of pulsating parameters and manipulator arrangement on the hydrodynamic coefficient,vibration response,motion trajectory,and vortex shedding behaviors were analyzed.Results indicated that the cross flow vibration displacement in pulsating flow increased by 32.14%compared to uniform flow,inducing a shift in the motion trajectory from a crescent shape to a sideward vase shape.In the absence of interference between the upper and lower arms,the lift coefficient of the manipulator substantially increased with rising pulsating frequency,reaching a maximum increment of 67.0%.This increase in the lift coefficient led to a 67.05%rise in the vibration frequency of the manipulator in the in-line direction.As the pulsating amplitude increased,the drag coefficient of the underwater manipulator rose by 36.79%,but the vibration frequency in the cross-flow direction decreased by 56.26%.Additionally,when the upper and lower arms remained in a state of mutual interference,the cross-flow vibration amplitudes of the upper and lower arms were approximately 1.84 and 4.82 times higher in a circular-elliptical arrangement compared to an elliptical-circular arrangement,respectively.Consequently,the flow field shifted from a P+S pattern to a disordered pattern,disrupting the regularity of the motion trajectory.
基金supported by the National Natural Science Foundation of China(42361144880)the Science and Technology Program of Xizang Autonomous Region,China(XZ202402ZD0001)the Qinghai Province Basic Research Program Project,China(2024-ZJ-904).
文摘Debris flow events are frequent in Tajikistan,yet comprehensive investigations at the regional scale are limited.This study integrates remote sensing,Geographic Information System,and machine learning techniques to evaluate debris flow susceptibility and associated hazards across Tajikistan.A dataset comprising 405 documented debris flow points and 14 influencing factors,encompassing geological,climatic-hydrological,and anthropogenic variables,was established.Three machine learning algorithms—Random Forest,Support Vector Machine(SVM),and Multi-layer Perceptron—were applied to generate susceptibility maps and delineate debris flow risk zones.The results indicate that the areas of higher and high susceptibility accounted for 20.43%and 4.41%of the national area,respectively,and were predominantly concentrated along the Zeravshan and Vakhsh river basins.Among the evaluated models,SVM model demonstrated the highest predictive performance.Beyond conventional topographic and environmental controls,drought conditions were identified as a critical factor influencing debris flow occurrence within the arid and semi-arid mountainous regions of Tajikistan.These findings provide a scientific basis for regional debris flow risk management and disaster mitigation planning,and offer practical guidance for selecting conditioning factors in machine-learning-based susceptibility assessments in other dry mountainous environments.
基金financial support provided by the Natural Science Foundation of Hebei Province,China(No.E2024105036)the Tangshan Talent Funding Project,China(Nos.B202302007 and A2021110015)+1 种基金the National Natural Science Foundation of China(No.52264042)the Australian Research Council(No.IH230100010)。
文摘Automated classification of gas flow states in blast furnaces using top-camera imagery typically demands a large volume of labeled data,whose manual annotation is both labor-intensive and cost-prohibitive.To mitigate this challenge,we present an enhanced semi-supervised learning approach based on the Mean Teacher framework,incorporating a novel feature loss module to maximize classification performance with limited labeled samples.The model studies show that the proposed model surpasses both the baseline Mean Teacher model and fully supervised method in accuracy.Specifically,for datasets with 20%,30%,and 40%label ratios,using a single training iteration,the model yields accuracies of 78.61%,82.21%,and 85.2%,respectively,while multiple-cycle training iterations achieves 82.09%,81.97%,and 81.59%,respectively.Furthermore,scenario-specific training schemes are introduced to support diverse deployment need.These findings highlight the potential of the proposed technique in minimizing labeling requirements and advancing intelligent blast furnace diagnostics.
文摘Reliable traffic flow prediction is crucial for mitigating urban congestion.This paper proposes Attentionbased spatiotemporal Interactive Dynamic Graph Convolutional Network(AIDGCN),a novel architecture integrating Interactive Dynamic Graph Convolution Network(IDGCN)with Temporal Multi-Head Trend-Aware Attention.Its core innovation lies in IDGCN,which uniquely splits sequences into symmetric intervals for interactive feature sharing via dynamic graphs,and a novel attention mechanism incorporating convolutional operations to capture essential local traffic trends—addressing a critical gap in standard attention for continuous data.For 15-and 60-min forecasting on METR-LA,AIDGCN achieves MAEs of 0.75%and 0.39%,and RMSEs of 1.32%and 0.14%,respectively.In the 60-min long-term forecasting of the PEMS-BAY dataset,the AIDGCN out-performs the MRA-BGCN method by 6.28%,4.93%,and 7.17%in terms of MAE,RMSE,and MAPE,respectively.Experimental results demonstrate the superiority of our pro-posed model over state-of-the-art methods.
基金supported by Science and Technology Project of the headquarters of the State Grid Corporation of China(No.5500-202324492A-3-2-ZN).
文摘To enhance power flow regulation in scenarios involving large-scale renewable energy transmission via high-voltage direct current(HVDC)links and multi-infeed DC systems in load-center regions,this paper proposes a hybrid modular multilevel converter–capacitor-commutated line-commutated converter(MMC-CLCC)HVDC transmission system and its corresponding control strategy.First,the system topology is constructed,and a submodule configuration method for the MMC—combining full-bridge submodules(FBSMs)and half-bridge submodules(HBSMs)—is proposed to enable direct power flow reversal.Second,a hierarchical control strategy is introduced,includingMMCvoltage control,CLCC current control,and a coordinationmechanism,along with the derivation of the hybrid system’s power flow reversal characteristics.Third,leveraging the CLCC’s fast current regulation and theMMC’s negative voltage control capability,a coordinated power flow reversal control strategy is developed.Finally,an 800 kV MMC-CLCC hybrid HVDC system is modeled in PSCAD/EMTDC to validate the power flow reversal performance under a high proportion of full-bridge submodule configuration.Results demonstrate that the proposed control strategy enables rapid(1-s transition)and smooth switching of bidirectional power flow without modifying the structure of primary equipment:the transient fluctuation ofDC voltage from the rated value(UdcN)to themaximumreverse voltage(-kUdcN)is less than 5%;the DC current strictly follows the preset characteristic curve with a deviation of≤3%;the active power reverses continuously,and the system maintains stable operation throughout the reversal process.
基金Supported by the National Natural Science Foundation of China(Grant No.40674063)National Hi-tech Research and Development Program of China(863Program)(Grant No.2006AA09Z311)
文摘Based on the synchronous joint gravity and magnetic inversion of single interface by Pilkington and the need of revealing Cenozoic and crystalline basement thickness in the new round of oil-gas exploration, we propose a joint gravity and magnetic inversion methodfor two-layer models by concentrating on the relationship between the change of thicknessI and position of the middle layer and anomaly and discuss the effects of the key parameters. Model tests and application to field data show the validity of this method.
文摘A model is proposed to evaluate the,effective modufi of a composite reinforced by two-layered spherical inclusions.This model is based on the localisation problem of a two- layered spherical inclusion embedded in an infinite matrix.The interations of the reinforced phases are taken into account by using the average matrix stress concept.When the external layer vanishes,the proposed model reduces to the classical Mori-Tanaka's model for spherical inclusions.Theoretical results for the composite of polyester matrix filled by hollow glass spheres and voids show excellent agreement with experimental results.
基金financial support from the Project of National Science Foundation of China(Grant No.41272346)the National Outstanding Youth Funds(Grant No.41225011)+2 种基金financial support from the Science & Technology Research Plan of China Railway Eryuan Engineering Group CO.LTD (Grant No.13164196(13-15))the Project of National Science Foundation of China(Grant Nos. 41472293,91430105)"hundred talents" program of CAS
文摘Many rock avalanches were triggered by the Wenchuan earthquake on May 12, 2008 in southwest China. Protection galleries covered with a single soil layer are usually used to protect against rockfall. Since one-layer protection galleries do not have sufficient buffer capacity, a two-layered absorbing system has been designed. This study aims to find whether an expanded poly-styrol （EPS） cushion, which is used in the soil-covered protection galleries for shock absorption, could be positioned under dynamic loadings. The dynamic impacts of the two-layered absorbing system under the conditions of rock avalanches are numerically simulated through a 2D discrete dement method. By selecting reasonable parameters, a series of numerical experiments were conducted to find the best combination for the two- layered absorbing system. The values of the EPS layer area as a percentage of the total area were set as 0% （Sl）, 22~ （S2）, and 70% （$3）. 22~ of the area of the EPS layer was found to be a reasonable value, and experiments were conducted to find the best position of the EPS layer in the two-layered absorbing system. The numerical results yield useful conclusions regarding the interaction between the impacting avalanches and the two-layered absorbing system. The soil layer can absorb the shock energy effectively and S2 （0.4-m thick EPS cushion covered with soil layer） is the most efficient combination, which can reduce the impact force, compared with the other combinations.
