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
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
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
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
To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator a...To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.展开更多
Vanadium redox flow batteries(VRFBs)are a means of large-scale energy storage due to their excellent scalability,safety,long cycling life,and decoupled power and energy capacities.However,the slow redox kinetics of va...Vanadium redox flow batteries(VRFBs)are a means of large-scale energy storage due to their excellent scalability,safety,long cycling life,and decoupled power and energy capacities.However,the slow redox kinetics of vanadium species on conventional carbon electrodes remains a major limitation to their performance.We investigated the deposition of carbon black,carbon nanotubes,and electrochemically exfoliated graphene(Exf-Gr)onto thermally-activated carbon paper(ACP)by spray coating to increase the electrode electrocatalytic activity.The modified electrodes were characterized using scanning electron microscopy,X-ray diffraction,Raman spectroscopy,X-ray photoelectron microscopy,and surface area analysis,while their electrochemical properties were evaluated by cyclic voltammetry,electrochemical impedance spectroscopy,and singlecell VRFB testing.Among the modified electrodes,Exf-Gr/ACP had the best performance,achieving a 2.9-fold reduction in charge transfer resistance compared to pristine ACP and delivering 2.5 times the discharge capacity in single-cell tests.This improvement is attributed to Exf-Gr’s high surface area,favorable catalytic activity,and excellent dispersion on the ACP substrate.Surface modification with electrochemically exfoliated graphene is a highly effective strategy for improving the electrode performance in VRFB systems,with significant implications for large-scale energy storage.展开更多
Large-eddy simulation(LES)is conducted to study the statistical properties of mixed-phase turbulence induced by the breaking of bow waves in flow past a partially submerged plate.The simulation is performed using a fi...Large-eddy simulation(LES)is conducted to study the statistical properties of mixed-phase turbulence induced by the breaking of bow waves in flow past a partially submerged plate.The simulation is performed using a finite difference method,with the air-water interface captured by a coupled level-set and volume-of-fluid method.Four cases are conducted to investigate the effects of Froude number on turbulent statistics,including the mean velocity,turbulence kinetic energy,and turbulence mass flux(TMF),which is an additional unclosed term in the Reynolds-averaged momentum equation.The TMF,especially its vertical component,shows a complex behaviour with respect to the Froude number.This property of the TMF imposes high demands on the robustness of the closure model of TMF.The present LES data is further used to examine a closure model of the TMF production term,which shows a high correlation with the data obtained from LES.展开更多
Multiscale mixing of the turbine blade tip leakage and mainstream flows causes considerable aerodynamic loss.Understanding it is crucial to correctly estimating the mixing loss and thus improving the turbine's per...Multiscale mixing of the turbine blade tip leakage and mainstream flows causes considerable aerodynamic loss.Understanding it is crucial to correctly estimating the mixing loss and thus improving the turbine's performance.The multiscale mixing phenomenon in a typical high-pressure turbine rotor flow was studied in this work.The contributions of various scale flows to entropy production and mixing properties were identified.The corresponding physical mechanisms at different scales were explored.It is shown that the large-scale and time-averaged flow contributions to mixing are significant,accounting for approximately 37.1% and 25% of the total.Time-averaged and large-scale flows cause the majority of the fluid deformation of the material surface,while mesoand small-scale flows just generate finer deformations.It raises the area stretch coefficient and the virtual concentration gradient.Thus,mixing is enhanced.Furthermore,time-averaged and large-scale flows account for the majority of the losses in the upstream and downstream regions of the blade tip respectively,accounting for approximately 53.8%and 33.5%of the total.The sheet-like structures—rather than the tip leaking vortex—are the primary source of the loss.High-dissipation regions are produced by the sheet-like structures via the pressure Hessian term and the self-amplification terms.展开更多
A 3D mathematical model was established to investigate the gas-liquid two-phase flow in Ruhrstahl-Heraeus(RH)vacuum refining process.The flow characteristics of molten steel were calculated using the coupled standard...A 3D mathematical model was established to investigate the gas-liquid two-phase flow in Ruhrstahl-Heraeus(RH)vacuum refining process.The flow characteristics of molten steel were calculated using the coupled standard k-εmodel and volume of fluid model.The bubble distribution was tracked by discrete phase model.Electromagnetic field was applied in the up-leg snorkel to enhance the effect of vacuum refining.The effect of swirling flow nozzles combined with electromagnetic stirring(EMS)on the flow characteristics of molten steel and bubble distribution was analyzed.The erosion of the up-leg snorkel was compared.The results show that when the swirling flow nozzles are used,the bubbles exhibit a distinct adherent rising behavior,and the refining efficiency decreases.In addition,the electromagnetic field can significantly improve the refining efficiency,but it brings stronger erosion to the up-leg snorkel.Nevertheless,when using the swirling flow nozzles combined with EMS,the refining performance is further optimized,and the erosion of the up-leg snorkel is also reduced due to its characteristic of bubble distribution.Compared to conventional nozzles,the mixing time was shortened by 16.2%,the recirculation rate increased by 12.5%.and the swirling intensity was strengthened by 8.9%.展开更多
Slug flow represents one of the most critical and operationally challenging regimes in oil-gas-water multiphase pipelines.To advance both mechanistic understanding and predictive capability,this study integrates physi...Slug flow represents one of the most critical and operationally challenging regimes in oil-gas-water multiphase pipelines.To advance both mechanistic understanding and predictive capability,this study integrates physical analysis with data-driven modeling to elucidate the conditions governing slug formation and to enable its rapid and accurate prediction.A systematic review of existing research is first undertaken to clarify the mechanisms responsible for slug initiation.The influences of gas superficial velocity,liquid velocity,liquid viscosity,liquid surface tension,and the axial component of gravity are examined to characterize their roles in interfacial instability and flow transition.Then,the effects of temperature,total flow rate,water cut,gas-liquid ratio,and pipeline inclination angle are quantitatively assessed,revealing the dominant trends that promote or inhibit slug development.Building on this foundation,a comprehensive three-phase oil-gas-water flow model is constructed.Numerical simulations are performed for 243 operating conditions encompassing a broad range of temperatures,water cuts,gas-liquid ratios,liquid flow rates,and inclination angles.These simulated cases constitute the training dataset for nine machine learning algorithms.To evaluate generalization performance,108 additional randomly generated operating conditions are predicted,covering temperatures of 80–150◦C,water cuts of 40–90%,gas-liquid ratios of 3–30,liquid flow rates of 100–200 t/d,and inclination angles of 5–15.Comparative validation reveals marked differences in predictive accuracy.The BP neural network achieves the highest accuracy,95%,substantially outperforming XGBoost,83.3%,Random Forest and Decision Tree,81.5%,Logistic Regression and Support Vector Machine,80.6%,K-Nearest Neighbor and Naive Bayes 78.7%,and K-Means,63%.Overall,the BP neural network demonstrates superior robustness and precision in predicting previously unseen operating conditions,effectively combining the physical consistency of mechanistic modeling with the efficiency and adaptability of machine learning approaches.展开更多
Interregional supply chains are associated with large carbon emissions,resulting in regional inequalities and sustainable development challenges.Quantifying interregional carbon flow is essential for setting equitable...Interregional supply chains are associated with large carbon emissions,resulting in regional inequalities and sustainable development challenges.Quantifying interregional carbon flow is essential for setting equitable carbon reduction targets and ensuring fairness among regions.However,as China advances its industrial transformation,the effects of industrial structural changes on regional carbon flow through supply chains remain insufficiently understood.Using Shanghai from 2012 to 2017 as a case study,this research investigates spatial patterns,sectoral characteristics and driving forces of carbon flow within interregional supply chains.Results reveal a 46.9%decrease in carbon inflows and a 70.2%increase in outflows,particularly to high-tech regions,indicating Shanghai's transition from a downstream recipient to an upstream supplier in industrial networks.Reduced inflows were mainly driven by decreased carbon intensity in northern energy and metal sectors,whereas increased outflows were associated with growing demand from southern equipment and construction industries.Energy structure optimization contributed to over 75%of carbon flow reductions,while increased carbon intensity in the digital economy accounted for only around 10%,insufficient to alter flow pathways.The findings indicates that industrial restructuring can support regional climate mitigation.As a pilot carbon trading cities with relatively low environmental cost,Shanghai can collaborate with other regions through carbon markets along key carbon pathways,leveraging financial resources for low-carbon technologies and promoting supply chain-wide emission reduction.This study provides a framework for designing targeted,region-specific mitigation strategies that align with the dynamics of industrial supply chains and contribute to equitable carbon reduction efforts.展开更多
To clarify fluid flow mechanisms and establish effective development conditions in continental shale oil reservoirs,a high-temperature,high-pressure steady-state flow system integrated with nuclear magnetic resonance(...To clarify fluid flow mechanisms and establish effective development conditions in continental shale oil reservoirs,a high-temperature,high-pressure steady-state flow system integrated with nuclear magnetic resonance(NMR)technology has been developed.The apparatus combines sample evacuation,rapid pressurization and saturation,and controlled displacement,enabling systematic investigation of single-phase shale oil flow under representative reservoir conditions.Related experiments allow proper quantification of the activation thresholds and relative contributions of different pore types to flow.A movable fluid index(MFI),defined using dual T_(2) cutoff values,is introduced accordingly and linked to key flow parameters.The results reveal distinct multi-scale characteristics of single-phase shale oil transport,namely micro-scale graded displacement and macro-scale segmented nonlinear behavior.As the injection-production pressure difference increases,flow pathways are activated progressively,beginning with fractures,followed by large and then smaller macropores,leading to a pronounced enhancement in apparent permeability.Although mesopores and micropores contribute little to direct flow,their indirect influence becomes increasingly important,and apparent permeability gradually approaches a stable limit at higher pressure difference.It is also shown that the MFI exhibits a strong negative correlation with the starting pressure gradient and a positive correlation with apparent permeability,providing a rapid and reliable indicator of shale oil flow capacity.Samples containing through-going fractures display consistently higher MFI values and superior flowability compared with those dominated by laminated fractures,highlighting the pivotal role of well-connected fracture networks generated by large-scale hydraulic fracturing in improving shale oil production.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 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.
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.
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.
文摘To investigate the influence of Al-Zn-Mg-Cu alloy with as-homogenized and as-rolled initial microstructures on the tensile flow behavior,isothermal tensile tests were conducted on a GLEEBLE-3500 isothermal simulator at temperatures of 380-440℃and strain rates of 0.05-1 s^(−1).The Johnson-Cook model,Hensel-Spittel model,strain-compensated Arrhenius model,and critical fracture strain model were established.Results show that through the evaluation of the models using the correlation coefficient(R)and the average absolute relative error,the strain-compensated Arrhenius model can represent the flow behavior of the alloy more accurately.Shear bands are more pronounced in the as-homogenized specimens,whereas dynamic recrystallization is predominantly observed in as-rolled specimens.Fracture morphology analysis reveals that a mixed fracture mechanism is prevalent in the as-homogenized specimen,whereas a ductile fracture mechanism is predominant in the as-rolled specimen.The processing maps indicate that the unstable region is reduced in the as-rolled specimens compared with that in the as-homogenized specimens.The optimal hot working windows for the as-homogenized and as-rolled specimens are determined as 410-440℃/0.14-1 s^(−1)and 380-400℃/0.05-0.29 s^(−1),respectively.
基金supported by the University of Seoul’s 2025 Research Fund.
文摘Vanadium redox flow batteries(VRFBs)are a means of large-scale energy storage due to their excellent scalability,safety,long cycling life,and decoupled power and energy capacities.However,the slow redox kinetics of vanadium species on conventional carbon electrodes remains a major limitation to their performance.We investigated the deposition of carbon black,carbon nanotubes,and electrochemically exfoliated graphene(Exf-Gr)onto thermally-activated carbon paper(ACP)by spray coating to increase the electrode electrocatalytic activity.The modified electrodes were characterized using scanning electron microscopy,X-ray diffraction,Raman spectroscopy,X-ray photoelectron microscopy,and surface area analysis,while their electrochemical properties were evaluated by cyclic voltammetry,electrochemical impedance spectroscopy,and singlecell VRFB testing.Among the modified electrodes,Exf-Gr/ACP had the best performance,achieving a 2.9-fold reduction in charge transfer resistance compared to pristine ACP and delivering 2.5 times the discharge capacity in single-cell tests.This improvement is attributed to Exf-Gr’s high surface area,favorable catalytic activity,and excellent dispersion on the ACP substrate.Surface modification with electrochemically exfoliated graphene is a highly effective strategy for improving the electrode performance in VRFB systems,with significant implications for large-scale energy storage.
基金supported by the National Natural Science Foundation of China(NSFC)Basic Science Center Program for‘Multiscale Problems in Nonlinear Mechanics’(Grant No.11988102)NSFC project(Grant No.11972038)Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-087).
文摘Large-eddy simulation(LES)is conducted to study the statistical properties of mixed-phase turbulence induced by the breaking of bow waves in flow past a partially submerged plate.The simulation is performed using a finite difference method,with the air-water interface captured by a coupled level-set and volume-of-fluid method.Four cases are conducted to investigate the effects of Froude number on turbulent statistics,including the mean velocity,turbulence kinetic energy,and turbulence mass flux(TMF),which is an additional unclosed term in the Reynolds-averaged momentum equation.The TMF,especially its vertical component,shows a complex behaviour with respect to the Froude number.This property of the TMF imposes high demands on the robustness of the closure model of TMF.The present LES data is further used to examine a closure model of the TMF production term,which shows a high correlation with the data obtained from LES.
基金supported by the National Science and Technology Major Project,China(No.J2019-Ⅱ-0012-0032)。
文摘Multiscale mixing of the turbine blade tip leakage and mainstream flows causes considerable aerodynamic loss.Understanding it is crucial to correctly estimating the mixing loss and thus improving the turbine's performance.The multiscale mixing phenomenon in a typical high-pressure turbine rotor flow was studied in this work.The contributions of various scale flows to entropy production and mixing properties were identified.The corresponding physical mechanisms at different scales were explored.It is shown that the large-scale and time-averaged flow contributions to mixing are significant,accounting for approximately 37.1% and 25% of the total.Time-averaged and large-scale flows cause the majority of the fluid deformation of the material surface,while mesoand small-scale flows just generate finer deformations.It raises the area stretch coefficient and the virtual concentration gradient.Thus,mixing is enhanced.Furthermore,time-averaged and large-scale flows account for the majority of the losses in the upstream and downstream regions of the blade tip respectively,accounting for approximately 53.8%and 33.5%of the total.The sheet-like structures—rather than the tip leaking vortex—are the primary source of the loss.High-dissipation regions are produced by the sheet-like structures via the pressure Hessian term and the self-amplification terms.
基金support from the National Natural Science Foundation of China(No.52174305).
文摘A 3D mathematical model was established to investigate the gas-liquid two-phase flow in Ruhrstahl-Heraeus(RH)vacuum refining process.The flow characteristics of molten steel were calculated using the coupled standard k-εmodel and volume of fluid model.The bubble distribution was tracked by discrete phase model.Electromagnetic field was applied in the up-leg snorkel to enhance the effect of vacuum refining.The effect of swirling flow nozzles combined with electromagnetic stirring(EMS)on the flow characteristics of molten steel and bubble distribution was analyzed.The erosion of the up-leg snorkel was compared.The results show that when the swirling flow nozzles are used,the bubbles exhibit a distinct adherent rising behavior,and the refining efficiency decreases.In addition,the electromagnetic field can significantly improve the refining efficiency,but it brings stronger erosion to the up-leg snorkel.Nevertheless,when using the swirling flow nozzles combined with EMS,the refining performance is further optimized,and the erosion of the up-leg snorkel is also reduced due to its characteristic of bubble distribution.Compared to conventional nozzles,the mixing time was shortened by 16.2%,the recirculation rate increased by 12.5%.and the swirling intensity was strengthened by 8.9%.
基金funded by the Hubei Provincial Department of Education Science and Technology Plan Project(Young and Middle-aged Talent Program)(https://jyt.hubei.gov.cn/),grant number Q20241308the National Natural Science Foundation of China(https://www.nsfc.gov.cn/),grant number 52174064.
文摘Slug flow represents one of the most critical and operationally challenging regimes in oil-gas-water multiphase pipelines.To advance both mechanistic understanding and predictive capability,this study integrates physical analysis with data-driven modeling to elucidate the conditions governing slug formation and to enable its rapid and accurate prediction.A systematic review of existing research is first undertaken to clarify the mechanisms responsible for slug initiation.The influences of gas superficial velocity,liquid velocity,liquid viscosity,liquid surface tension,and the axial component of gravity are examined to characterize their roles in interfacial instability and flow transition.Then,the effects of temperature,total flow rate,water cut,gas-liquid ratio,and pipeline inclination angle are quantitatively assessed,revealing the dominant trends that promote or inhibit slug development.Building on this foundation,a comprehensive three-phase oil-gas-water flow model is constructed.Numerical simulations are performed for 243 operating conditions encompassing a broad range of temperatures,water cuts,gas-liquid ratios,liquid flow rates,and inclination angles.These simulated cases constitute the training dataset for nine machine learning algorithms.To evaluate generalization performance,108 additional randomly generated operating conditions are predicted,covering temperatures of 80–150◦C,water cuts of 40–90%,gas-liquid ratios of 3–30,liquid flow rates of 100–200 t/d,and inclination angles of 5–15.Comparative validation reveals marked differences in predictive accuracy.The BP neural network achieves the highest accuracy,95%,substantially outperforming XGBoost,83.3%,Random Forest and Decision Tree,81.5%,Logistic Regression and Support Vector Machine,80.6%,K-Nearest Neighbor and Naive Bayes 78.7%,and K-Means,63%.Overall,the BP neural network demonstrates superior robustness and precision in predicting previously unseen operating conditions,effectively combining the physical consistency of mechanistic modeling with the efficiency and adaptability of machine learning approaches.
基金supported by the National Natural Science Foundation of China[grant numbers 52270185,41971257].
文摘Interregional supply chains are associated with large carbon emissions,resulting in regional inequalities and sustainable development challenges.Quantifying interregional carbon flow is essential for setting equitable carbon reduction targets and ensuring fairness among regions.However,as China advances its industrial transformation,the effects of industrial structural changes on regional carbon flow through supply chains remain insufficiently understood.Using Shanghai from 2012 to 2017 as a case study,this research investigates spatial patterns,sectoral characteristics and driving forces of carbon flow within interregional supply chains.Results reveal a 46.9%decrease in carbon inflows and a 70.2%increase in outflows,particularly to high-tech regions,indicating Shanghai's transition from a downstream recipient to an upstream supplier in industrial networks.Reduced inflows were mainly driven by decreased carbon intensity in northern energy and metal sectors,whereas increased outflows were associated with growing demand from southern equipment and construction industries.Energy structure optimization contributed to over 75%of carbon flow reductions,while increased carbon intensity in the digital economy accounted for only around 10%,insufficient to alter flow pathways.The findings indicates that industrial restructuring can support regional climate mitigation.As a pilot carbon trading cities with relatively low environmental cost,Shanghai can collaborate with other regions through carbon markets along key carbon pathways,leveraging financial resources for low-carbon technologies and promoting supply chain-wide emission reduction.This study provides a framework for designing targeted,region-specific mitigation strategies that align with the dynamics of industrial supply chains and contribute to equitable carbon reduction efforts.
基金supported by the National Science and Technology Major Project of China(Grant No.2024ZD 1004302)the Key Scientific and Technological Research project of SINOPEC(Grant No.P25186).
文摘To clarify fluid flow mechanisms and establish effective development conditions in continental shale oil reservoirs,a high-temperature,high-pressure steady-state flow system integrated with nuclear magnetic resonance(NMR)technology has been developed.The apparatus combines sample evacuation,rapid pressurization and saturation,and controlled displacement,enabling systematic investigation of single-phase shale oil flow under representative reservoir conditions.Related experiments allow proper quantification of the activation thresholds and relative contributions of different pore types to flow.A movable fluid index(MFI),defined using dual T_(2) cutoff values,is introduced accordingly and linked to key flow parameters.The results reveal distinct multi-scale characteristics of single-phase shale oil transport,namely micro-scale graded displacement and macro-scale segmented nonlinear behavior.As the injection-production pressure difference increases,flow pathways are activated progressively,beginning with fractures,followed by large and then smaller macropores,leading to a pronounced enhancement in apparent permeability.Although mesopores and micropores contribute little to direct flow,their indirect influence becomes increasingly important,and apparent permeability gradually approaches a stable limit at higher pressure difference.It is also shown that the MFI exhibits a strong negative correlation with the starting pressure gradient and a positive correlation with apparent permeability,providing a rapid and reliable indicator of shale oil flow capacity.Samples containing through-going fractures display consistently higher MFI values and superior flowability compared with those dominated by laminated fractures,highlighting the pivotal role of well-connected fracture networks generated by large-scale hydraulic fracturing in improving shale oil production.
