Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This...Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.展开更多
A thermodynamically complete multi-phase equation of state(EOS)applicable to both dense and porous metals at wide ranges of temperature and pressure is constructed.A standard three-term decomposition of the Helmholtz ...A thermodynamically complete multi-phase equation of state(EOS)applicable to both dense and porous metals at wide ranges of temperature and pressure is constructed.A standard three-term decomposition of the Helmholtz free energy as a function of specific volume and temperature is presented,where the cold component models both compression and expansion states,the thermal ion component introduces the Debye approximation and melting entropy,and the thermal electron component employs the Thomas-Fermi-Kirzhnits(TFK)model.The porosity of materials is considered by introducing the dynamic porosity coefficientαand the constitutive P-αrelation,connecting the thermodynamic properties between dense and porous systems,allowing for an accurate description of the volume decrease caused by void collapse while maintaining the quasi-static thermodynamic properties of porous systems identical to the dense ones.These models enable the EOS applicable and robust at wide ranges of temperature,pressure and porosity.A systematic evaluation of the new EOS is conducted with aluminum(Al)as an example.300 K isotherm,shock Hugoniot,as well as melting curves of both dense and porous Al are calculated,which shows great agreements with experimental data and validates the effectiveness of the models and the accuracy of parameterizations.Notably,it is for the first time Hugoniot P-σcurves up to 10~6 GPa and shock melting behaviors of porous Al are derived from analytical EOS models,which predict much lower compression limit and shock melting temperatures than those of dense Al.展开更多
The nitrate reduction via electrochemical catalysis offers an environmentally friendly method for sustainable ammonia production and wastewater remediation.However,conventional Co-based catalysts suffer from a major l...The nitrate reduction via electrochemical catalysis offers an environmentally friendly method for sustainable ammonia production and wastewater remediation.However,conventional Co-based catalysts suffer from a major limitation:their nitrate(NO_(3)^(-))adsorption capacity remains weak.This drawback severely restricts their catalytic efficiency.To overcome this limitation,we synthesized a triphasic interface material(Cu/Co/CoO@C)via rapid joule heating and elucidated its performance-enhancing mechanisms.The exceptional catalytic performance originates from the phase interface-induced multiscale structural regulation.At the microscopic scale,electronic structure modulation through interfacial charge redistribution between Cu and Co/CoO significantly reduces intermediate adsorption energies.Co 3d and O 2p orbitals coupling generates a localized polarized electric field,enhancing NO_(3)^(-)activation.At the macroscopic scale,defect-rich structures improve mass transfer and expose abundant active sites.With the Cu/Co/CoO@C,the yield of NH_(3) is achieved to 2.03 mmol h^(-1)cm^(-2)(-0.4 V vs.RHE,Faradaic efficiency(FE)98.4%).The assembled Zn-NO_(3)^(-)battery delivered a maximum power density of 52.09 mW cm^(-2)and a NH_(3) production rate of 297.5μmol h^(-1)cm^(-2)(FE 95.4%).Based on these results,this work offers new insights into multiphase interface design.展开更多
Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to in...Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to inherent fluctuations,limited data and imperfect measurements resulting in aleatory,epistemic and measurement uncertainties of the degradation process.This paper proposes a degradation model and remaining useful life(RUL)prediction method under triple uncertainties for a category of complex equipment with multi-phase degradation and jumps.First,a multi-phase degradation model with random jumps and measurement errors is constructed based on uncertain random processes.Afterward,the analytic expression of RUL prediction considering the heterogeneity is derived by modeling the uncertainty of degradation states at change points under the concept of first hitting time.A stochastic uncertain approach is utilized for the proposed multi-phase degradation model to identify model parameters based on historical data.Furthermore,the implied degradation features are adaptively updated in online stage using similarity-based weighted stochastic uncertain maximum likelihood estimation and Kalman filtering.Finally,the effectiveness of the method is verified by simulation example and practical case.展开更多
The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recogni...The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.展开更多
Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a c...Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.展开更多
1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(I...1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(IL),and enhancement of upper stopband rejection(Huang et al.,2021;Snyder et al.,2021;Lin et al.,2023;Zeng et al.,2023).展开更多
In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the...In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.展开更多
Color filters are essential components for optical modulation.However,conventional filters are restricted to operating exclusively in either reflective or transmissive mode.Furthermore,they suffer from limited UV and ...Color filters are essential components for optical modulation.However,conventional filters are restricted to operating exclusively in either reflective or transmissive mode.Furthermore,they suffer from limited UV and thermal stability,low color purity,and exhibit identical coloration on both surfaces.Herein,we propose a novel design strategy for trans-reflective color filters by integrating the absorptive properties of dye-doped polysulfone(PSU)with the diffractive capabilities of photonic crystals.This composite filter achieved broad-spectrum transmission with deep color outputs—yellow(0.410,0.510),magenta(0.446,0.231),and cyan(0.201,0.425)—closely aligned with standard color space coordinates.By tuning the refractive index of CeO_(2)@SiO_(2)nanoparticles to match dye-based PSU matrix,the transmittance of filters exceeded 70%.Moreover,dye-mediated absorption reduces the scattering light,thereby enhancing reflection color purity(full width at half maxima(FWHM)=25 nm)and producing vibrant blue,green,and red hues.The incorporation of UV-absorbing CeO_(2)@SiO_(2)nanoparticles effectively mitigated dye photodegradation,yielding exceptional UV stability(ΔT<2%under prolonged UV exposure).The filters also exhibited outstanding thermal stability(ΔT<1%after 30 min heat treatment at 230°C).This work establishes a robust materials design framework for multifunctional optical filters,advancing the development of highfidelity dual-mode color systems for next-generation display technologies.展开更多
Recommendation systems are an integral and indispensable part of every digital platform,as they can suggest content or items to users based on their respective needs.Collaborative filtering is a technique often used i...Recommendation systems are an integral and indispensable part of every digital platform,as they can suggest content or items to users based on their respective needs.Collaborative filtering is a technique often used in various studies,which produces recommendations by analyzing similarities between users and items based on their behavior.Although often used,traditional collaborative filtering techniques still face the main challenge of sparsity.Sparsity problems occur when the data in the system is sparse,meaning that only a portion of users provide feedback on some items,resulting in inaccurate recommendations generated by the system.To overcome this problem,we developed aHybrid Collaborative Filtering model based onMatrix Factorization andGradient Boosting(HCF-MFGB),a new hybrid approach.Our proposed model integrates SVD++,the XGBoost ensemble learning algorithm,and utilizes user demographic data and meta items.We utilize information,both explicitly and implicitly,to learn user preference patterns using SVD++.The XGBoost algorithm is used to create hundreds of decision trees incrementally,thereby improving model accuracy.Meanwhile,user demographic and meta-item data are clustered using the K-Means Clustering algorithm to capture similarities in user and item characteristics.This combination is designed to improve rating prediction accuracy by reducing reliance on minimal explicit rating data,while addressing sparsity issues in movie recommendation systems.The results of experiments on the MovieLens 100K,MovieLens 1M,and CiaoDVD datasets show significant improvements,outperforming various other baselinemodels in terms of RMSE and MAE.On theMovieLens 100K dataset,the HCF-MFGB model obtained an RMSE value of 0.853 and an MAE value of 0.674.On theMovieLens 1M dataset,the HCF-MFGB model obtained an RMSE value of 0.763 and an MAE value of 0.61.On the CiaoDCD dataset,the HCF-MFGB model achieved an RMSE value of 0.718 and an MAE value of 0.495.These results confirm a significant improvement in movie recommendation accuracy with the proposed approach.展开更多
This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temp...This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.展开更多
A new multi-phase active contour model is proposed for the image segmentation. It is a generalization of the C-V model with the following characteristics： （1） A key technique, called the technique of painting backg...A new multi-phase active contour model is proposed for the image segmentation. It is a generalization of the C-V model with the following characteristics： （1） A key technique, called the technique of painting background （TPBG）, is developed to remove the information of the background, which blocks the detection of weak boundaries in the object; （2） The two-phase level set is applied multiple times for getting the multi-phase segmentation model （n-1 times for the n-phase model, n〉1）; （3） A scaling-based method is introduced to improve the basic model. Experimental results show that the proposed model is effective for detecting weak boundaries.展开更多
A capacity model of multi-phase signalized intersections is derived by a stopping-line method. It is simplified with two normal situations： one situation involves one straight lane and one left-turn lane; the other s...A capacity model of multi-phase signalized intersections is derived by a stopping-line method. It is simplified with two normal situations： one situation involves one straight lane and one left-turn lane; the other situation involves two straight lanes and one left-turn lane. The results show that the capacity is mainly relative to signal cycle length, phase length, intersection layout and following time. With regard to the vehicles arrival rates, the optimal model is derived based on each phase＇s remaining time balance, and it is solved by Lagrange multipliers. Therefore, the calculation models of the optimal signal cycle length and phase lengths are derived and simplified. Compared to the existing models, the proposed model is more convenient and practical. Finally, a practical intersection is chosen and its signal cycles and phase lengths are calculated by the proposed model.展开更多
The fluid of casting process is a typical kind of multi-phase flow. Actually, many casting phenomena have close relationship with the multi-phase flow, such as molten metal filling process, air entrapment, slag moveme...The fluid of casting process is a typical kind of multi-phase flow. Actually, many casting phenomena have close relationship with the multi-phase flow, such as molten metal filling process, air entrapment, slag movement, venting process of die casting, gas escaping of lost foam casting and so on. Obviously, in order to analyze these phenomena accurately, numerical simulation of the multi-phase fluid is necessary. Unfortunately, so far, most of the commercial casting simulation systems do not have the ability of multi-phase flow modeling due to the difficulty in the multi-phase flow calculation. In the paper, Finite Different Method (FDM) technique was adopt to solve the multi-phase fluid model. And a simple object of the muiti-phase fluid was analyzed to obtain the fluid rates of the liquid phase and the entrapped air phase.展开更多
The hydrocarbon detection techniques used currently are generally based on the theory of single-phase medium, but hydrocarbon reservoir mostly is multi-phase medium, therefore, multisolutions and uncertainties are exi...The hydrocarbon detection techniques used currently are generally based on the theory of single-phase medium, but hydrocarbon reservoir mostly is multi-phase medium, therefore, multisolutions and uncertainties are existed in the result of hydrocarbon detection. This paper presents a fast way to detect hydrocarbon in accordance with BOIT theory and laboratory data. The technique called DHAF technique has been applied to several survey area and obtained good result where the coincidence rate for hydrocarbon detection is higher than other similar techniques. The method shows a good prospect of the application in hydrocarbon detecting at exploration stage and in reservoir monitoring at production stage.展开更多
Polyamide/acrylonitrile-butadiene-styrene copolymer(PA/ABS) blends have drawn considerable attention from both academia and industry for their important applications in automotive and electronic areas. Due to poor mis...Polyamide/acrylonitrile-butadiene-styrene copolymer(PA/ABS) blends have drawn considerable attention from both academia and industry for their important applications in automotive and electronic areas. Due to poor miscibility of PA and ABS, developing an effective compatibilization strategy has been an urgent challenge to achieve prominent mechanical properties. In this study, we create a set of mechanically enhanced PA6/ABS blends using two multi-monomer melt-grafted compatibilizers, SEBSg-(MAH-co-St) and ABS-g-(MAH-co-St). The dispersed domain size is significantly decreased and meanwhile the unique "soft shell-encapsulating-hard core" structures form in the presence of compatibilizers. The optimum mechanical performances manifest an increase of 36% in tensile strength and an increase of 1300% in impact strength, compared with the neat PA6/ABS binary blend.展开更多
In the petroleum industry,detection of multi-phase fluid flow is very important in both surface and down-hole measurements.Accurate measurement of high rate of water or gas multi-phase flow has always been an academic...In the petroleum industry,detection of multi-phase fluid flow is very important in both surface and down-hole measurements.Accurate measurement of high rate of water or gas multi-phase flow has always been an academic and industrial focus.NMR is an efficient and accurate technique for the detection of fluids;it is widely used in the determination of fluid compositions and properties.This paper is aimed to quantitatively detect multi-phase flow in oil and gas wells and pipelines and to propose an innovative method for online nuclear magnetic resonance(NMR)detection.The online NMR data acquisition,processing and interpretation methods are proposed to fill the blank of traditional methods.A full-bore straight tube design without pressure drop,a Halbach magnet structure design with zero magnetic leakage outside the probe,a separate antenna structure design without flowing effects on NMR measurement and automatic control technology will achieve unattended operation.Through the innovation of this work,the application of NMR for the real-time and quantitative detection of multi-phase flow in oil and gas wells and pipelines can be implemented.展开更多
The rapid construction of artificial reservoirs in metropolises has promoted the emergence of city-river-reservoir systems worldwide.This study investigated the environmental behaviors and risks of heavy metals in the...The rapid construction of artificial reservoirs in metropolises has promoted the emergence of city-river-reservoir systems worldwide.This study investigated the environmental behaviors and risks of heavy metals in the aquatic environment of a typical system composed of main watersheds in Suzhou and Jinze Reservoir in Shanghai.Results shown that Mn,Zn and Cu were the dominant metals detected in multiple phases.Cd,Mn and Zn were mainly presented in exchangeable fraction and exhibited high bioavailability.Great proportion and high mobility of metals were found in suspended particulate matter(SPM),suggesting that SPM can greatly affect metal multi-phase distribution process.Spatially,city system(Ci S)exhibited more serious metal pollution and higher ecological risk than river system(Ri S)and reservoir system(Re S)owing to the diverse emission sources.Ci S and Re S were regarded as critical pollution source and sink,respectively,while Ri S was a vital transportation aisle.Microbial community in sediments exhibited evident spatial variation and obviously modified by exchangeable metals and nutrients.In particular,Bacteroidetes and Firmicutes presented significant positive correlations with most exchangeable metals.Risk assessment implied that As,Sb and Ni in water may pose potential carcinogenic risk to human health.Nevertheless,Re S was in a fairly safe state.Hg was the main risk contributor in SPM,while Cu,Zn,Ni and Sb showed moderate risk in sediments.Overall,Hg,Sb and Ci S were screened out as priority metals and system,respectively.More attention should be paid to these priority issues to promote the sustainable development of the watershed.展开更多
Based on the fundamental equations of the mechanics of solid continuum,the paper employs an analytical model for determination of elastic thermal stresses in isotropic continuum represented by periodically distributed...Based on the fundamental equations of the mechanics of solid continuum,the paper employs an analytical model for determination of elastic thermal stresses in isotropic continuum represented by periodically distributed spherical particles with different distributions in an infinite matrix,imaginarily divided into identical cells with dimensions equal to inter-particle distances,containing a central spherical particle with or without a spherical envelope on the particle surface.Consequently,the multi-particle-(envelope)-matrix system,as a model system regarding the analytical modelling,is applicable to four types of multi-phase materials.As functions of the particle volume fraction v,the inter-particle distances dl,d2,d3 along three mutually per-pendicular axes,and the particle and envelope radii,R1 and R2,respectively,the thermal stresses within the cell,are originated during a cooling process as a consequence of the difference in thermal expansion coefficients of phases rep-resented by the matrix,envelope and particle.Analytical-(experimental)-computational lifetime prediction methods for multi-phase materials are proposed,which can be used in engineering with appropriate values of parameters of real multi-phase materials.展开更多
Batch processes are usually involved with multiple phases in the time domain and many researches on process monitoring as well as quality prediction have been done using phase information. However, few of them conside...Batch processes are usually involved with multiple phases in the time domain and many researches on process monitoring as well as quality prediction have been done using phase information. However, few of them consider phase transitions, though they exit widely in batch processes and have non-ignorable impacts on product qualities. In the present work, a phase-based partial least squares (PLS) method utilizing transition information is proposed to give both online and offline quality predictions. First, batch processes are divided into several phases using regression parameters other than prior process knowledge. Then both steady phases and transitions which have great influences on qualities are identified as critical-to-quality phases using statistical methods. Finally, based on the analysis of different characteristics of transitions and steady phases, an integrated algorithm is developed for quality prediction. The application to an injection molding process shows the effectiveness of the proposed algorithm in comparison with the traditional MPLS method and the phase-based PLS method.展开更多
基金supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(Project No.15308024)a grant from Research Centre for Carbon-Strategic Catalysis,The Hong Kong Polytechnic University(CE2X).
文摘Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12205023,U2230401,12374056,U23A20537,11904027)。
文摘A thermodynamically complete multi-phase equation of state(EOS)applicable to both dense and porous metals at wide ranges of temperature and pressure is constructed.A standard three-term decomposition of the Helmholtz free energy as a function of specific volume and temperature is presented,where the cold component models both compression and expansion states,the thermal ion component introduces the Debye approximation and melting entropy,and the thermal electron component employs the Thomas-Fermi-Kirzhnits(TFK)model.The porosity of materials is considered by introducing the dynamic porosity coefficientαand the constitutive P-αrelation,connecting the thermodynamic properties between dense and porous systems,allowing for an accurate description of the volume decrease caused by void collapse while maintaining the quasi-static thermodynamic properties of porous systems identical to the dense ones.These models enable the EOS applicable and robust at wide ranges of temperature,pressure and porosity.A systematic evaluation of the new EOS is conducted with aluminum(Al)as an example.300 K isotherm,shock Hugoniot,as well as melting curves of both dense and porous Al are calculated,which shows great agreements with experimental data and validates the effectiveness of the models and the accuracy of parameterizations.Notably,it is for the first time Hugoniot P-σcurves up to 10~6 GPa and shock melting behaviors of porous Al are derived from analytical EOS models,which predict much lower compression limit and shock melting temperatures than those of dense Al.
基金financial support provided by the National Natural Science Foundation of Yunnan Province(202301AS070040,202301AU070209)the Major Science and Technology Projects of Yunnan Province(202302AB080019-3)+3 种基金the Scientific Research Fund Project of Yunnan Provincial Department of Education(2023J0033)the Laboratory of Solid-State Ions for Green Energy of Yunnan Universitythe Analysis and Measurements Center of Yunnan University for the sample testing servicethe Electron Microscope Center of Yunnan University for the support of this work。
文摘The nitrate reduction via electrochemical catalysis offers an environmentally friendly method for sustainable ammonia production and wastewater remediation.However,conventional Co-based catalysts suffer from a major limitation:their nitrate(NO_(3)^(-))adsorption capacity remains weak.This drawback severely restricts their catalytic efficiency.To overcome this limitation,we synthesized a triphasic interface material(Cu/Co/CoO@C)via rapid joule heating and elucidated its performance-enhancing mechanisms.The exceptional catalytic performance originates from the phase interface-induced multiscale structural regulation.At the microscopic scale,electronic structure modulation through interfacial charge redistribution between Cu and Co/CoO significantly reduces intermediate adsorption energies.Co 3d and O 2p orbitals coupling generates a localized polarized electric field,enhancing NO_(3)^(-)activation.At the macroscopic scale,defect-rich structures improve mass transfer and expose abundant active sites.With the Cu/Co/CoO@C,the yield of NH_(3) is achieved to 2.03 mmol h^(-1)cm^(-2)(-0.4 V vs.RHE,Faradaic efficiency(FE)98.4%).The assembled Zn-NO_(3)^(-)battery delivered a maximum power density of 52.09 mW cm^(-2)and a NH_(3) production rate of 297.5μmol h^(-1)cm^(-2)(FE 95.4%).Based on these results,this work offers new insights into multiphase interface design.
基金supported by the National Key Research and Development Program of China(2021YFB3301200)the National Natural Science Foundation of China(NSFC)(U21A20483,62373040,62203042).
文摘Due to abrupt changes in the intrinsic degradation mechanism or shock from external environmental pressure,degradations of some equipment are characterized by multi-phase and jumps.Meanwhile,equipment is subject to inherent fluctuations,limited data and imperfect measurements resulting in aleatory,epistemic and measurement uncertainties of the degradation process.This paper proposes a degradation model and remaining useful life(RUL)prediction method under triple uncertainties for a category of complex equipment with multi-phase degradation and jumps.First,a multi-phase degradation model with random jumps and measurement errors is constructed based on uncertain random processes.Afterward,the analytic expression of RUL prediction considering the heterogeneity is derived by modeling the uncertainty of degradation states at change points under the concept of first hitting time.A stochastic uncertain approach is utilized for the proposed multi-phase degradation model to identify model parameters based on historical data.Furthermore,the implied degradation features are adaptively updated in online stage using similarity-based weighted stochastic uncertain maximum likelihood estimation and Kalman filtering.Finally,the effectiveness of the method is verified by simulation example and practical case.
文摘The Savitzky-Golay(SG)filter,which employs polynomial least-squares approximations to smooth data and estimate derivatives,is widely used for processing noisy data.However,noise suppression by the SG filter is recognized to be limited at data boundaries and high frequencies,which can significantly reduce the signal-to-noise ratio(SNR).To solve this problem,a novel method synergistically integrating Principal Component Analysis(PCA)with SG filtering is proposed in this paper.This approach avoids the is-sue of excessive smoothing associated with larger window sizes.The proposed PCA-SG filtering algorithm was applied to a CO gas sensing system based on Cavity Ring-Down Spectroscopy(CRDS).The perform-ance of the PCA-SG filtering algorithm is demonstrated through comparison with Moving Average Filtering(MAF),Wavelet Transformation(WT),Kalman Filtering(KF),and the SG filter.The results demonstrate that the proposed algorithm exhibits superior noise reduction capabilities compared to the other algorithms evaluated.The SNR of the ring-down signal was improved from 11.8612 dB to 29.0913 dB,and the stand-ard deviation of the extracted ring-down time constant was reduced from 0.037μs to 0.018μs.These results confirm that the proposed PCA-SG filtering algorithm effectively improves the smoothness of the ring-down curve data,demonstrating its feasibility.
基金supported by the Royal Academy of Engineering,UK,in the scheme of Distinguished International Associate(DIA-2424-5-134).
文摘Accurate estimation of the State of Charge(SOC),State of Health(SOH),and Terminal Resistance(TR)is crucial for the effective operation of Battery Management Systems(BMS)in lithium-ion batteries.This study conducts a comprehensive comparative analysis of four Kalman filter variants Extended Kalman Filter(EKF),Extended Kalman-Bucy Filter(EKBF),Unscented Kalman Filter(UKF),and Unscented Kalman-Bucy Filter(UKBF)under varying battery parameter conditions.These include temperature fluctuation,self-discharge,current direction,cell capacity,process noise,and measurement noise.Our findings reveal significant variations in the performance of SOC and SOH predictions across filters,emphasizing that UKF demonstrates superior robustness to noise,while EKF performs better under accurate system dynamics.The study underscores the need for adaptive filtering strategies that can dynamically adjust to evolving battery parameters,thereby enhancing BMS reliability and extending battery lifespan.
基金supported by the National Natural Science Foundation of China(No.62371263)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCK25_1995).
文摘1 Introduction Recently,the increasing demand for advanced telecommunication systems has spurred extensive research into bandpass filters(BPFs),with particular emphasis on miniaturization,reduction of insertion loss(IL),and enhancement of upper stopband rejection(Huang et al.,2021;Snyder et al.,2021;Lin et al.,2023;Zeng et al.,2023).
基金Supported by the Guangxi Special Program for Technological Innovation Guidance(No.GuiKeAC25069006).
文摘In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.
基金supported by the Program of the National Natural Science Foundation of China(22238002)the Fundamental Research Funds for the Central Universities(DUT22-LAB610)Research and Innovation Team Project of Dalian University of Technology(DUT2022TB10).
文摘Color filters are essential components for optical modulation.However,conventional filters are restricted to operating exclusively in either reflective or transmissive mode.Furthermore,they suffer from limited UV and thermal stability,low color purity,and exhibit identical coloration on both surfaces.Herein,we propose a novel design strategy for trans-reflective color filters by integrating the absorptive properties of dye-doped polysulfone(PSU)with the diffractive capabilities of photonic crystals.This composite filter achieved broad-spectrum transmission with deep color outputs—yellow(0.410,0.510),magenta(0.446,0.231),and cyan(0.201,0.425)—closely aligned with standard color space coordinates.By tuning the refractive index of CeO_(2)@SiO_(2)nanoparticles to match dye-based PSU matrix,the transmittance of filters exceeded 70%.Moreover,dye-mediated absorption reduces the scattering light,thereby enhancing reflection color purity(full width at half maxima(FWHM)=25 nm)and producing vibrant blue,green,and red hues.The incorporation of UV-absorbing CeO_(2)@SiO_(2)nanoparticles effectively mitigated dye photodegradation,yielding exceptional UV stability(ΔT<2%under prolonged UV exposure).The filters also exhibited outstanding thermal stability(ΔT<1%after 30 min heat treatment at 230°C).This work establishes a robust materials design framework for multifunctional optical filters,advancing the development of highfidelity dual-mode color systems for next-generation display technologies.
基金funded by the Directorate General of Research and Development,Ministry of Higher Education,Science and Technology of the Republic of Indonesia,with grant number 2.6.63/UN32.14.1/LT/2025.
文摘Recommendation systems are an integral and indispensable part of every digital platform,as they can suggest content or items to users based on their respective needs.Collaborative filtering is a technique often used in various studies,which produces recommendations by analyzing similarities between users and items based on their behavior.Although often used,traditional collaborative filtering techniques still face the main challenge of sparsity.Sparsity problems occur when the data in the system is sparse,meaning that only a portion of users provide feedback on some items,resulting in inaccurate recommendations generated by the system.To overcome this problem,we developed aHybrid Collaborative Filtering model based onMatrix Factorization andGradient Boosting(HCF-MFGB),a new hybrid approach.Our proposed model integrates SVD++,the XGBoost ensemble learning algorithm,and utilizes user demographic data and meta items.We utilize information,both explicitly and implicitly,to learn user preference patterns using SVD++.The XGBoost algorithm is used to create hundreds of decision trees incrementally,thereby improving model accuracy.Meanwhile,user demographic and meta-item data are clustered using the K-Means Clustering algorithm to capture similarities in user and item characteristics.This combination is designed to improve rating prediction accuracy by reducing reliance on minimal explicit rating data,while addressing sparsity issues in movie recommendation systems.The results of experiments on the MovieLens 100K,MovieLens 1M,and CiaoDVD datasets show significant improvements,outperforming various other baselinemodels in terms of RMSE and MAE.On theMovieLens 100K dataset,the HCF-MFGB model obtained an RMSE value of 0.853 and an MAE value of 0.674.On theMovieLens 1M dataset,the HCF-MFGB model obtained an RMSE value of 0.763 and an MAE value of 0.61.On the CiaoDCD dataset,the HCF-MFGB model achieved an RMSE value of 0.718 and an MAE value of 0.495.These results confirm a significant improvement in movie recommendation accuracy with the proposed approach.
文摘This article presents an adaptive intelligent control strategy applied to a lumped-parameter evaporator model,i.e.,a simplified dynamic representation treating the evaporator as a single thermal node with uniform temperature distribution,suitable for control design due to its balance between physical fidelity and computational simplicity.The controller uses a wavelet-based neural proportional,integral,derivative(PID)controller with IIR filtering(infinite impulse response).The dynamic model captures the essential heat and mass transfer phenomena through a nonlinear energy balance,where the cooling capacity“Qevap”is expressed as a non-linear function of the compressor frequency and the temperature difference,specifically,Q_(evap)=k_(1)u(T_(in)−T_(e))with u as compressor frequency,Te evaporator temperature,and Tin inlet fluid temperature.The operating conditions of the system,in general terms,focus on the following variables,the overall thermal capacity is 1000 J/K,typical for small-capacity heat exchangers,The mass flow is 0.05 kg/s,typical for secondary liquid cooling circuits,the overall loss coefficient of 50 W/K that corresponds to small evaporators with partial insulation,the temperatures(inlet)of 10℃and the temperature of environment of 25℃,thermal load of 200 W that corresponds to a small-scaled air conditioning applications.To handle system nonlinearities and improve control performance,aMorlet wavelet-based neural network(Wavenet)is used to dynamically adjust the PID gains online.An IIR filter is incorporated to smooth the adaptive gains,improving stability and reducing oscillations.In contrast to prior wavelet-or neural-adaptive PID controllers in HVAC applications,which typically adjust gains without explicit filtering or not tailored to evaporator dynamics,this work introduces the first PID–Wavenet scheme augmented with an IIR-based stabilization layer,specifically designed to address the combined challenges of nonlinear evaporator behavior,gain oscillation,and real-time implementability.The proposed controller(PID-Wavenet+IIR)is implemented and validated inMATLAB/Simulink,demonstrating superior performance compared to a conventional PID tuned using Simulink’s auto-tuning function.Key results include a reduction in settling time from 13.3 to 8.2 s,a reduction in overshoot from 3.5%to 0.8%,a reduction in steady-state error from 0.12℃ to 0.02℃and a 13%reduction in energy overall consumption.The controller also exhibits greater robustness and adaptability under varying thermal loads.This explicit integration of wavelet-driven adaptation with IIR-filtered gain shaping constitutes the main methodological contribution and novelty of the work.These findings validate the effectiveness of the wavelet-based adaptive approach for advanced thermal management in refrigeration and HVAC systems,with potential applications in controlling variable-speed compressors,liquid chillers,and compact cooling units.
文摘A new multi-phase active contour model is proposed for the image segmentation. It is a generalization of the C-V model with the following characteristics： （1） A key technique, called the technique of painting background （TPBG）, is developed to remove the information of the background, which blocks the detection of weak boundaries in the object; （2） The two-phase level set is applied multiple times for getting the multi-phase segmentation model （n-1 times for the n-phase model, n〉1）; （3） A scaling-based method is introduced to improve the basic model. Experimental results show that the proposed model is effective for detecting weak boundaries.
基金China Postdoctoral Science Foundation(No.2004035208)Jiangsu Communication Science Foundation (No.06Y36)
文摘A capacity model of multi-phase signalized intersections is derived by a stopping-line method. It is simplified with two normal situations： one situation involves one straight lane and one left-turn lane; the other situation involves two straight lanes and one left-turn lane. The results show that the capacity is mainly relative to signal cycle length, phase length, intersection layout and following time. With regard to the vehicles arrival rates, the optimal model is derived based on each phase＇s remaining time balance, and it is solved by Lagrange multipliers. Therefore, the calculation models of the optimal signal cycle length and phase lengths are derived and simplified. Compared to the existing models, the proposed model is more convenient and practical. Finally, a practical intersection is chosen and its signal cycles and phase lengths are calculated by the proposed model.
文摘The fluid of casting process is a typical kind of multi-phase flow. Actually, many casting phenomena have close relationship with the multi-phase flow, such as molten metal filling process, air entrapment, slag movement, venting process of die casting, gas escaping of lost foam casting and so on. Obviously, in order to analyze these phenomena accurately, numerical simulation of the multi-phase fluid is necessary. Unfortunately, so far, most of the commercial casting simulation systems do not have the ability of multi-phase flow modeling due to the difficulty in the multi-phase flow calculation. In the paper, Finite Different Method (FDM) technique was adopt to solve the multi-phase fluid model. And a simple object of the muiti-phase fluid was analyzed to obtain the fluid rates of the liquid phase and the entrapped air phase.
基金The project is sponsored by the Innovation Foundation of Key Lab of Geophysical Exploration under CNPC.
文摘The hydrocarbon detection techniques used currently are generally based on the theory of single-phase medium, but hydrocarbon reservoir mostly is multi-phase medium, therefore, multisolutions and uncertainties are existed in the result of hydrocarbon detection. This paper presents a fast way to detect hydrocarbon in accordance with BOIT theory and laboratory data. The technique called DHAF technique has been applied to several survey area and obtained good result where the coincidence rate for hydrocarbon detection is higher than other similar techniques. The method shows a good prospect of the application in hydrocarbon detecting at exploration stage and in reservoir monitoring at production stage.
基金the National Natural Science Foundation of China (No. 51633003) for the financial support
文摘Polyamide/acrylonitrile-butadiene-styrene copolymer(PA/ABS) blends have drawn considerable attention from both academia and industry for their important applications in automotive and electronic areas. Due to poor miscibility of PA and ABS, developing an effective compatibilization strategy has been an urgent challenge to achieve prominent mechanical properties. In this study, we create a set of mechanically enhanced PA6/ABS blends using two multi-monomer melt-grafted compatibilizers, SEBSg-(MAH-co-St) and ABS-g-(MAH-co-St). The dispersed domain size is significantly decreased and meanwhile the unique "soft shell-encapsulating-hard core" structures form in the presence of compatibilizers. The optimum mechanical performances manifest an increase of 36% in tensile strength and an increase of 1300% in impact strength, compared with the neat PA6/ABS binary blend.
基金supported by the National Natural Science Foundation of China(Grant No.51704327)
文摘In the petroleum industry,detection of multi-phase fluid flow is very important in both surface and down-hole measurements.Accurate measurement of high rate of water or gas multi-phase flow has always been an academic and industrial focus.NMR is an efficient and accurate technique for the detection of fluids;it is widely used in the determination of fluid compositions and properties.This paper is aimed to quantitatively detect multi-phase flow in oil and gas wells and pipelines and to propose an innovative method for online nuclear magnetic resonance(NMR)detection.The online NMR data acquisition,processing and interpretation methods are proposed to fill the blank of traditional methods.A full-bore straight tube design without pressure drop,a Halbach magnet structure design with zero magnetic leakage outside the probe,a separate antenna structure design without flowing effects on NMR measurement and automatic control technology will achieve unattended operation.Through the innovation of this work,the application of NMR for the real-time and quantitative detection of multi-phase flow in oil and gas wells and pipelines can be implemented.
基金supported by the Scientific and Innovative Action Plan of Shanghai(CN)“One Belt One Road”International Cooperation Project(No.20260750400)the Singapore National Research Foundation(NRF)under its Campus for Research Excellence and Technological Enterprise(CREATE)program(E2S2-CREATE project ES-2:Detection,Assessment&Modelling of Emerging Contaminants in the Urban Environment)。
文摘The rapid construction of artificial reservoirs in metropolises has promoted the emergence of city-river-reservoir systems worldwide.This study investigated the environmental behaviors and risks of heavy metals in the aquatic environment of a typical system composed of main watersheds in Suzhou and Jinze Reservoir in Shanghai.Results shown that Mn,Zn and Cu were the dominant metals detected in multiple phases.Cd,Mn and Zn were mainly presented in exchangeable fraction and exhibited high bioavailability.Great proportion and high mobility of metals were found in suspended particulate matter(SPM),suggesting that SPM can greatly affect metal multi-phase distribution process.Spatially,city system(Ci S)exhibited more serious metal pollution and higher ecological risk than river system(Ri S)and reservoir system(Re S)owing to the diverse emission sources.Ci S and Re S were regarded as critical pollution source and sink,respectively,while Ri S was a vital transportation aisle.Microbial community in sediments exhibited evident spatial variation and obviously modified by exchangeable metals and nutrients.In particular,Bacteroidetes and Firmicutes presented significant positive correlations with most exchangeable metals.Risk assessment implied that As,Sb and Ni in water may pose potential carcinogenic risk to human health.Nevertheless,Re S was in a fairly safe state.Hg was the main risk contributor in SPM,while Cu,Zn,Ni and Sb showed moderate risk in sediments.Overall,Hg,Sb and Ci S were screened out as priority metals and system,respectively.More attention should be paid to these priority issues to promote the sustainable development of the watershed.
基金the Slovak Research and Development Agency under the contract No.COST-0022-06,APVV-51-061505the 6th FP EU NESPA+5 种基金the Slovak Grant Agency VEGA(2/7197/27,2/7194/27,2/7195/27)NANOSMART,Centre of Excellence(1/1/2007-31/12/2010)Slovak Academy of Sciences,by KMM-NoE 502243-2(10/2004-9/2008)NENAMAT INCO-CT-2003-510363COST Action 536 and COST Action 538János Bolyai Research Grant NSF-MTA-OTKA grant-MTA:96/OTKA:049953,OTKA 63609
文摘Based on the fundamental equations of the mechanics of solid continuum,the paper employs an analytical model for determination of elastic thermal stresses in isotropic continuum represented by periodically distributed spherical particles with different distributions in an infinite matrix,imaginarily divided into identical cells with dimensions equal to inter-particle distances,containing a central spherical particle with or without a spherical envelope on the particle surface.Consequently,the multi-particle-(envelope)-matrix system,as a model system regarding the analytical modelling,is applicable to four types of multi-phase materials.As functions of the particle volume fraction v,the inter-particle distances dl,d2,d3 along three mutually per-pendicular axes,and the particle and envelope radii,R1 and R2,respectively,the thermal stresses within the cell,are originated during a cooling process as a consequence of the difference in thermal expansion coefficients of phases rep-resented by the matrix,envelope and particle.Analytical-(experimental)-computational lifetime prediction methods for multi-phase materials are proposed,which can be used in engineering with appropriate values of parameters of real multi-phase materials.
基金Supported by Guangzhou Nansha District Bureau of Economy & Trade, Science & Technology, Information, Project (201103003)the Fundamental Research Funds for the Central Universities (2012QNA5012)+1 种基金Project of Education Department of Zhejiang Province (Y201223159)Technology Foundation for Selected Overseas Chinese Scholar of Zhejiang Province (J20120561)
文摘Batch processes are usually involved with multiple phases in the time domain and many researches on process monitoring as well as quality prediction have been done using phase information. However, few of them consider phase transitions, though they exit widely in batch processes and have non-ignorable impacts on product qualities. In the present work, a phase-based partial least squares (PLS) method utilizing transition information is proposed to give both online and offline quality predictions. First, batch processes are divided into several phases using regression parameters other than prior process knowledge. Then both steady phases and transitions which have great influences on qualities are identified as critical-to-quality phases using statistical methods. Finally, based on the analysis of different characteristics of transitions and steady phases, an integrated algorithm is developed for quality prediction. The application to an injection molding process shows the effectiveness of the proposed algorithm in comparison with the traditional MPLS method and the phase-based PLS method.
