Polymer electrolyte membrane fuel cells(PEMFCs)are considered a promising alternative to internal combustion engines in the automotive sector.Their commercialization is mainly hindered due to the cost and effectivenes...Polymer electrolyte membrane fuel cells(PEMFCs)are considered a promising alternative to internal combustion engines in the automotive sector.Their commercialization is mainly hindered due to the cost and effectiveness of using platinum(Pt)in them.The cathode catalyst layer(CL)is considered a core component in PEMFCs,and its composition often considerably affects the cell performance(V_(cell))also PEMFC fabrication and production(C_(stack))costs.In this study,a data-driven multi-objective optimization analysis is conducted to effectively evaluate the effects of various cathode CL compositions on Vcelland Cstack.Four essential cathode CL parameters,i.e.,platinum loading(L_(Pt)),weight ratio of ionomer to carbon(wt_(I/C)),weight ratio of Pt to carbon(wt_(Pt/c)),and porosity of cathode CL(ε_(cCL)),are considered as the design variables.The simulation results of a three-dimensional,multi-scale,two-phase comprehensive PEMFC model are used to train and test two famous surrogates:multi-layer perceptron(MLP)and response surface analysis(RSA).Their accuracies are verified using root mean square error and adjusted R^(2).MLP which outperforms RSA in terms of prediction capability is then linked to a multi-objective non-dominated sorting genetic algorithmⅡ.Compared to a typical PEMFC stack,the results of the optimal study show that the single-cell voltage,Vcellis improved by 28 m V for the same stack price and the stack cost evaluated through the U.S department of energy cost model is reduced by$5.86/k W for the same stack performance.展开更多
The hepatitis B virus(HBV)is considered to be a major public health problem worldwide,and a significant number of reports on nosocomial outbreaks of HBV infections have been reported.Prevention of indirect HBV transmi...The hepatitis B virus(HBV)is considered to be a major public health problem worldwide,and a significant number of reports on nosocomial outbreaks of HBV infections have been reported.Prevention of indirect HBV transmission by contaminated objects is only possible through the use of infection-control principles,including the use of chemical biocides,which are proven to render the virus non-infectious.The virucidal activity of biocides against HBV cannot be predicted;therefore,validation of the virucidal action of disinfectants against HBV is essential.However,feasible HBV infectivity assays have not yet been established.Thus,surrogate models have been proposed for testing the efficacy of biocides against HBV.Most of these assays do not correlate with HBV infectivity.Currently,the most promising and feasible assay is the use of the taxonomically related duck hepatitis B virus(DHBV),which belongs to the same Hepadnaviridae virus family.This paper reviews the application of DHBV,which can be propagated in vitro in primary duck embryonic hepatocytes,for the testing of biocides and describes why this model can be used as reliable method to evaluate disinfectants for efficacy against HBV.The susceptibility levels of important biocides,which are often used as ingredients for commercially available disinfectants,are also described.展开更多
The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precisio...The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.展开更多
Successful embryo implantation requires highly coordinated maternal-embryo interactions.Implantation failure is a major factor contributing to infertility.However,the mechanism underlying implantation failure remains ...Successful embryo implantation requires highly coordinated maternal-embryo interactions.Implantation failure is a major factor contributing to infertility.However,the mechanism underlying implantation failure remains unclear.An improved understanding of the early implantation process not only improves the success rate of assisted reproductive treatments but also helps in studying the pathophysiology of reproductive disorders.Owing to ethical concerns,in vivo studies of human embryo implantation are not feasible.However,the results obtained from animal models cannot be directly applied to humans.Over the years,in vitro implantation models have been developed to investigate implantation mechanisms.In this review,we discuss the use of different models for generating embryo-like surrogates to study early embryo development and implantation in vitro,with a specific focus on stem cell-derived blastocyst-like embryo surrogates.There is no definitive evidence that the recently established embryo-like models re-capitulate all developmental events of human embryos during the peri-implantation stage.Regardless,stem cell-derived embryo surrogates are the most valuable tools for studying the mechanisms of early cell lineage differentiation and developmental failures during implantation.展开更多
Evaluation of damage evolution effects in biodegradable pure Mg was carried out,using transmission electron microscope as surrogate irradiation for high-energy radionuclide β decay in Brachytherapy.Time-dependent qua...Evaluation of damage evolution effects in biodegradable pure Mg was carried out,using transmission electron microscope as surrogate irradiation for high-energy radionuclide β decay in Brachytherapy.Time-dependent quantitative defect production,evolution dynamics,and evolution statistics were revealed in-situ for two prism foils(z=[1.210],[10.10]),in as-received and heat-treated pure Mg,after 300 keV electron irradiation up to 0.468 dpa at R.T.Preferred nucleation of basal-plane interstitial-type 1/6<20.23>loops was confirmed,in addition to a small portion of prism-plane 1/3<11.20>loops.No cavities were found.A higher yield of point defect concentration and a more evident trend of defect coarsening were identified in[1.210]than in[10.10].Pre-existing dislocations(on the orders of 10^(13)−10^(14) m^(−2))in pure Mg resulted in a delay of the first occurrence of visible defects.Defect migration and elastic interactions governed the microstructural evolution of electron irradiation damage in pure Mg,giving rise to events of loop coalescence,growth,and sometimes rotation of habit plane.The influence of incident electron energy can be correlated to the rates of point defect production,and is quantifiable;however,interfered by defect cluster stability,defect mobility,and defect interactions.This forms an important theoretical basis for the application of Mg subjected to MeV-level β-decay radiation in Brachytherapy.The paper concludes with a brief comparison between Mg and conventional Ti casing,outlines the advantages and challenges,and provides reference points for the validation of Mg/Mg-alloys in Brachytherapy seed application.展开更多
Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the s...Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the solar array.It is necessary to accurately predict the output power of the array for any flight state.Because of the uneven solar radiation received by the solar array,the traditional model based on components has a slow simulation speed.In this study,a data-driven surrogate modeling approach for prediction the output power of the solar array is proposed.The surrogate model is trained using the samples obtained from the high-accuracy simulation model.By using the input parameter preprocessor,the accuracy of the surrogate model in predicting the output power of the solar array is improved to 98.65%.In addition,the predictive speed of the surrogate model is ten million times faster than the traditional simulation model.Finally,the surrogate model is used to predict the energy balance of stratospheric airships flying throughout the year under actual global wind fields.展开更多
Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determ...Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determines the trans-medium flight vehicle performance.To quantitatively analyze the flight vehicle performance,an entire aerial-aquatic trajectory model is developed in this paper.Different from modeling a trajectory purely for the water entry process,the constructed entire trajectory model has integrated aerial,water entry,and underwater trajectories together,which can consider the influence of the connected trajectories.As for the aerial and underwater trajectories,explicit dynamic models are established to obtain the trajectory parameters.Due to the complicated fluid force during high-velocity water entry,a computational fluid dynamics model is investigated to analyze this phase.The compu-tational domain size is adaptively refined according to the final aerial trajectory state,where the redundant computational domain is removed.An entire trajectory optimization problem is then formulated to maximize the total flight range via tuning the joint states of different trajectories.Simultaneously,several constraints,i.e.,the max impact load,trajectory height,etc.,are involved in the optimization problem.Rather than directly optimizing by a heuristic algorithm,a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem.In this method,various surrogates coopera-tively generate infill sample points,thereby preventing the poor approximation.After optimization,the total flight range can be improved by 20%,while all the constraints are satisfied.The result demonstrates the effectiveness and practicability of the developed model and optimization framework.展开更多
Objective:A conventional endpoint for locally advanced cervical cancer(LACC)clinical trials is overall survival(OS)with five years of follow-up.The primary hypothesis was that progression-free survival(PFS)with three ...Objective:A conventional endpoint for locally advanced cervical cancer(LACC)clinical trials is overall survival(OS)with five years of follow-up.The primary hypothesis was that progression-free survival(PFS)with three years of follow-up(PFS36)would be an appropriate primary surrogate endpoint.Materials and methods:The primary hypothesis,which was developed from our data,was further investigated using phase III randomized controlled trials and then externally validated using retrospective studies up to 2023.Correlation analysis at the treatment-arm level was performed between 2-,3-,4-,and 5-year PFS rates and 5-year OS.Results:A total of 613 patients with histologically confirmed cervical cancer who underwent radiotherapy or chemoradiation at our institute between January 2010 and December 2013 were eligible.The recurrence rates for years 1 through 5 were 12.9%,7.3%,3%,2.3%,and 1.8%,respectively.Patients who did not achieve PFS36 had a 5-year OS rate of 30.3%.However,patients who achieved PFS36 had a 5-year OS rate of 98.2%.Further data were extracted from 26 randomized phase III trials on LACC.The trials included 55 arms,with a pooled sample size of 7,281 patients.Trial-level surrogacy results revealed that PFS36(r2,0.732)was associated with 5-year OS.The correlation between PFS36 and OS was externally validated using independent retrospective data.Conclusion:A significant positive correlation was found between PFS36 and OS at 5 years of follow-up both within patients and across trials.These results suggest that PFS36 is an appropriate endpoint for LACC clinical trials of radiotherapy-based regimens.展开更多
The authors regret that the original publication of this paper did not include Jawad Fayaz as a co-author.After further discussions and a thorough review of the research contributions,it was agreed that his significan...The authors regret that the original publication of this paper did not include Jawad Fayaz as a co-author.After further discussions and a thorough review of the research contributions,it was agreed that his significant contributions to the foundational aspects of the research warranted recognition,and he has now been added as a co-author.展开更多
The production optimization in the closed-loop reservoir management is generally empirical,and challenged by the issues such as low precision,low efficiency,and difficulty in solving constrained optimization problems....The production optimization in the closed-loop reservoir management is generally empirical,and challenged by the issues such as low precision,low efficiency,and difficulty in solving constrained optimization problems.This paper outlines the main principles,advantages and disadvantages of commonly used production optimization methods/models,and then proposes an intelligent integrated production optimization method for waterflooding reservoirs that considers efficiency and precision,real-time and long-term effects,and the interaction and synergy between a variety of optimization models.This method integrates multiple optimization methods/models,such as reservoir performance analysis,reduced-physics models,and reservoir numerical models,with these model results and insights organically coupled to facilitate model construction and matching.This proposed method is elucidated and verified by field examples.The findings indicate that the optimal production optimization model varies depending on the specific application scenario.Reduced-physics models are conducive to short-term real-time optimization,whereas the simulator-based surrogate optimization and streamline-based simulation optimization methods are more suitable for long-term optimization strategy formulation,both of which need to be implemented under reasonable constraints from the perspective of reservoir engineering in order to be of practical value.展开更多
This paper aims to design a morphing wing with both Flexible Leading Edge(FLE)and Flexible Trailing Edge(FTE)by using cellular structures,which can help the wing boost the deformation to a greater extent on the premis...This paper aims to design a morphing wing with both Flexible Leading Edge(FLE)and Flexible Trailing Edge(FTE)by using cellular structures,which can help the wing boost the deformation to a greater extent on the premise that the weight is not changed,so as to play a greater role in aerodynamic control such as gust interference.First,as for structural design,based on NACA0012,a morphing wing model constructed by 3 forms of cell structures is proposed.Then,the aerodynamic characteristics under the interference of FLE and FTE are calculated by the Computational Fluid Dynamic(CFD)method.After the surrogate model is established to predict the lift coefficient of the wing effectively,the sensitivity analysis reveals that the main sensitivity index of FTE deflection angle β is 0.565,which has the greatest influence on the lift coefficient.And the total sensitivity index of FLE deflection angle γ is increased by 78.9%,which reveals a strong coupling relationship between FLE and FTE.Finally,using Finite Element Analysis(FEA)method and experiment,the deformation capability of the model under certain static loads are obtained.The results reveal that the maximum deflection angle of the morphing wing model can be±22°at FLE and±64°at FTE,indicating strong structural stiffness and resistance to bending breakage of the model.The presented results can be useful in the design of the cellular morphing wing with multiple flexible systems.展开更多
Coalbed methane(CBM)is a vital unconventional energy resource,and predicting its spatiotemporal pressure dynamics is crucial for efficient development strategies.This paper proposes a novel deep learningebased data-dr...Coalbed methane(CBM)is a vital unconventional energy resource,and predicting its spatiotemporal pressure dynamics is crucial for efficient development strategies.This paper proposes a novel deep learningebased data-driven surrogate model,AxialViT-ConvLSTM,which integrates AxialAttention Vision Transformer,ConvLSTM,and an enhanced loss function to predict pressure dynamics in CBM reservoirs.The results showed that the model achieves a mean square error of 0.003,a learned perceptual image patch similarity of 0.037,a structural similarity of 0.979,and an R^(2) of 0.982 between predictions and actual pressures,indicating excellent performance.The model also demonstrates strong robustness and accuracy in capturing spatialetemporal pressure features.展开更多
In the realm of subsurface flow simulations,deep-learning-based surrogate models have emerged as a promising alternative to traditional simulation methods,especially in addressing complex optimization problems.However...In the realm of subsurface flow simulations,deep-learning-based surrogate models have emerged as a promising alternative to traditional simulation methods,especially in addressing complex optimization problems.However,a significant challenge lies in the necessity of numerous high-fidelity training simulations to construct these deep-learning models,which limits their application to field-scale problems.To overcome this limitation,we introduce a training procedure that leverages transfer learning with multi-fidelity training data to construct surrogate models efficiently.The procedure begins with the pre-training of the surrogate model using a relatively larger amount of data that can be efficiently generated from upscaled coarse-scale models.Subsequently,the model parameters are finetuned with a much smaller set of high-fidelity simulation data.For the cases considered in this study,this method leads to about a 75%reduction in total computational cost,in comparison with the traditional training approach,without any sacrifice of prediction accuracy.In addition,a dedicated well-control embedding model is introduced to the traditional U-Net architecture to improve the surrogate model's prediction accuracy,which is shown to be particularly effective when dealing with large-scale reservoir models under time-varying well control parameters.Comprehensive results and analyses are presented for the prediction of well rates,pressure and saturation states of a 3D synthetic reservoir system.Finally,the proposed procedure is applied to a field-scale production optimization problem.The trained surrogate model is shown to provide excellent generalization capabilities during the optimization process,in which the final optimized net-present-value is much higher than those from the training data ranges.展开更多
Accurate acquisition of the rock stress is crucial for various rock engineering applications.The hollow inclusion (HI) technique is widely used for measuring in-situ rock stress.This technique calculates the stress te...Accurate acquisition of the rock stress is crucial for various rock engineering applications.The hollow inclusion (HI) technique is widely used for measuring in-situ rock stress.This technique calculates the stress tensor by measuring strain using an HI strain cell.However,existing analytical solutions for stress calculation based on an HI strain cell in a double-layer medium are not applicable when an HI strain cell is used in a three-layer medium,leading to erroneous stress calculations.To address this issue,this paper presents a method for calculating stress tensors in a three-layer medium using numerical simulations,specifically by obtaining a constitutive matrix that relates strain measurements to stress tensors in a three-layer medium.Furthermore,using Latin hypercube sampling (LHS) and orthogonal experimental design strategies,764 groups of numerical models encompassing various stress measurement scenarios have been established and calculated using FLAC^(3D)software.Finally,a surrogate model based on artificial neural network (ANN) was developed to predict constitutive matrices,achieving a goodness of fit (R^(2)) of 0.999 and a mean squared error (MSE) of 1.254.A software program has been developed from this surrogate model for ease of use in practical engineering applications.The method’s accuracy was verified through numerical simulations,analytical solution and laboratory experiment,demonstrating its effectiveness in calculating stress in a three-layer medium.The surrogate model was applied to calculate mining-induced stress in the roadway roof rock of a coal mine,a typical case for stress measurement in a three-layer medium.Errors in stress calculations arising from the use of existing analytical solutions were corrected.The study also highlights the significant errors associated with using double-layer analytical solutions in a three-layer medium,which could lead to inappropriate engineering design.展开更多
During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a com...During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a complex,unsteady flow phenomenon highly sensitive to inlet conditions such asMach and Reynolds numbers.The key features of three-dimensional blade stall can be effectively represented by the dynamic stall behavior of a pitching airfoil.In this study,we conduct an uncertainty quantification analysis of dynamic stall aerodynamics in high-Mach-number flows over pitching airfoils,accounting for uncertainties in inlet parameters.A computational fluid dynamics(CFD)model based on the compressible unsteady Reynolds-averagedNavier–Stokes(URANS)equations,coupledwith sliding mesh techniques,is developed to simulate the unsteady aerodynamic behavior and associated flow fields.To efficiently capture the aerodynamic responses while maintaining high accuracy,a multi-fidelity Co-Kriging surrogate model is constructed.This model integrates the precision of high-fidelity wind tunnel experiments with the computational efficiency of lower-fidelity URANS simulations.Its accuracy is validated through direct comparison with experimental data.Building upon this surrogate model,we employ interval analysis and the Sobol sensitivity method to quantify the uncertainty and parameter sensitivity of the unsteady aerodynamic forces resulting frominlet condition variability.Both the inlet Mach number and Reynolds number are treated as uncertain inputs,modeled using interval representations.Our results demonstrate that variations inMach number contribute far more significantly to aerodynamic uncertainty than those in Reynolds number.Moreover,the presence of dynamic stall vortices markedly amplifies the aerodynamic sensitivity to Mach number fluctuations.展开更多
The surrogate model serves as an efficient simulation tool during the slope parameter inversion process.However,the creep constitutive model integrated with dynamic damage evolution poses challenges in development of ...The surrogate model serves as an efficient simulation tool during the slope parameter inversion process.However,the creep constitutive model integrated with dynamic damage evolution poses challenges in development of the required surrogate model.In this study,a novel physics knowledge-based surrogate model framework is proposed.In this framework,a Transformer module is employed to capture straindriven softening-hardening physical mechanisms.Positional encoding and self-attention are utilized to transform the constitutive parameters associated with shear strain,which are not directly time-related,into intermediate latent features for physical loss calculation.Next,a multi-layer stacked GRU(gated recurrent unit)network is built to provide input interfaces for time-dependent intermediate latent features,hydraulic boundary conditions,and water-rock interaction degradation equations,with static parameters introduced via external fully-connected layers.Finally,a combined loss function is constructed to facilitate the collaborative training of physical and data loss,introducing time-dependent weight adjustments to focus the surrogate model on accurate deformation predictions during critical phases.Based on the deformation of a reservoir bank landslide triggered by impoundment and subsequent restabilization,an elasto-viscoplastic constitutive model that considers water effect and sliding state dependencies is developed to validate the proposed surrogate model framework.The results indicate that the framework exhibits good performance in capturing physical mechanisms and predicting creep behavior,reducing errors by about 30 times compared to baseline models such as GRU and LSTM(long short-term memory),meeting the precision requirements for parameter inversion.Ablation experiments also confirmed the effectiveness of the framework.This framework can also serve as a reference for constructing other creep surrogate models that involve non-time-related across dimensions.展开更多
This study proposes a multi-objective optimization framework for electric winches in fiber-reinforced plastic(FRP)fishing vessels to address critical limitations of conventional designs,including excessive weight,mate...This study proposes a multi-objective optimization framework for electric winches in fiber-reinforced plastic(FRP)fishing vessels to address critical limitations of conventional designs,including excessive weight,material inefficiency,and performance redundancy.By integrating surrogate modeling techniques with a multi-objective genetic algorithm(MOGA),we have developed a systematic approach that encompasses parametric modeling,finite element analysis under extreme operational conditions,and multi-fidelity performance evaluation.Through a 10-t electric winch case study,the methodology’s effectiveness is demonstrated via parametric characterization of structural integrity,stiffness behavior,and mass distribution.The comparative analysis identified optimal surrogate models for predicting key performance metrics,which enabled the construction of a robust multi-objective optimization model.The MOGA-derived Pareto solutions produced a design configuration achieving 7.86%mass reduction,2.01%safety factor improvement,and 23.97%deformation mitigation.Verification analysis confirmed the optimization scheme’s reliability in balancing conflicting design requirements.This research establishes a generalized framework for marine deck machinery modernization,particularly addressing the structural compatibility challenges in FRP vessel retrofitting.The proposed methodology demonstrates significant potential for facilitating sustainable upgrades of fishing vessel equipment through systematic performance optimization.展开更多
Simultaneously,reducing an acoustic metamaterial’s weight and sound pressure level is an important but difficult topic.Considering the law of mass,traditional lightweight acoustic metamaterials make it difficult to c...Simultaneously,reducing an acoustic metamaterial’s weight and sound pressure level is an important but difficult topic.Considering the law of mass,traditional lightweight acoustic metamaterials make it difficult to control noise efficiently in real-life applications.In this study,a novel optimization-driven design scheme is developed to obtain lightweight acoustic metamaterials with a strong sound insulation capability for additive manufacturing.In the proposed design scheme,a topology optimization method for an acoustic metamaterial in the acoustic-solid interaction system is implemented to obtain an initial cross-sectional topology of the acoustic microstructure during the conceptual design phase.Then,in the detailed design phase,the parametric model for a higher-dimensional design is formulated based on the topology optimization result.An adaptive Kriging interpolation approach is proposed to accurately reformulate a much easier surrogate model from the original parameterization formulation to avoid repeating calls for nonlinear analyses in the 3D acoustic-structure interaction system.A surrogate model was used to optimize a ready-to-print acoustic metamaterial with improved noise reduction performance.Experimental verification based on an impedance tube is implemented.Results demonstrate characteristics of the devised metamaterial as well as the proposed method.展开更多
The rapid development of evolutionary deep learning has led to the emergence of various Neural Architecture Search(NAS)algorithms designed to optimize neural network structures.However,these algorithms often face sign...The rapid development of evolutionary deep learning has led to the emergence of various Neural Architecture Search(NAS)algorithms designed to optimize neural network structures.However,these algorithms often face significant computational costs due to the time-consuming process of training neural networks and evaluating their performance.Traditional NAS approaches,which rely on exhaustive evaluations and large training datasets,are inefficient for solving complex image classification tasks within limited time frames.To address these challenges,this paper proposes a novel NAS algorithm that integrates a hierarchical evaluation strategy based on Surrogate models,specifically using supernet to pre-trainweights and randomforests as performance predictors.This hierarchical framework combines rapid Surrogate model evaluations with traditional,precise evaluations to balance the trade-off between performance accuracy and computational efficiency.The algorithm significantly reduces the time required for model evaluation by predicting the fitness of candidate architectures using a random forest Surrogate model,thus alleviating the need for full training cycles for each architecture.The proposed method also incorporates evolutionary operations such as mutation and crossover to refine the search process and improve the accuracy of the resulting architectures.Experimental evaluations on the CIFAR-10 and CIFAR-100 datasets demonstrate that the proposed hierarchical evaluation strategy reduces the search time and costs compared to traditional methods,while achieving comparable or even superior model performance.The results suggest that this approach can efficiently handle resourceconstrained tasks,providing a promising solution for accelerating the NAS process without compromising the quality of the generated architectures.展开更多
Low collateral damage weapons achieve controlled personnel injury through the coupling of shock waves and particle swarms,where the particle swarms arise from the high-explosive dispersion of compacted metal particle ...Low collateral damage weapons achieve controlled personnel injury through the coupling of shock waves and particle swarms,where the particle swarms arise from the high-explosive dispersion of compacted metal particle ring.To investigate the dynamic response of the human target under combined shock waves and particle swarms loading,a physical human surrogate torso model(HSTM)was developed,and the dynamic response test experiment was conducted under the combined loading.The effects of particle size on the loading parameters,the damage patterns of the ballistic plate and HSTM,and the dynamic response parameters of the HSTM with and without protection are mainly analyzed.Our findings revealed that particle swarms can effectively delay the shock wave attenuation,especially the best effect when the particle size was 0.28–0.45 mm.The ballistic plate mainly exhibited dense perforation of the outer fabric and impacted crater damage of ceramic plates,whereas the unprotected HSTM was mainly dominated by high-density and small-size ballistic cavity group damage.The peak values of the dynamic response parameters for the HSTM under combined loading were significantly larger than those under bare charge loading,with multiple peaks observed.Under unprotected conditions,the peak acceleration of skeletons and peak pressure of organs increased with the particle size.Under protected conditions,the particle size,the number of particles hit,and the fit of the ballistic plate to the HSTM together affected the dynamic response parameters of the HSTM.展开更多
基金supported by the Technology Innovation Program of the Korea Evaluation Institute of Industrial Technology (KEIT)under the Ministry of Trade,Industry and Energy (MOTIE)of Republic of Korea (20012121)by the National Research Foundation of Korea (NRF)grant funded by the Korea government (MSIT) (2022M3J7A106294)。
文摘Polymer electrolyte membrane fuel cells(PEMFCs)are considered a promising alternative to internal combustion engines in the automotive sector.Their commercialization is mainly hindered due to the cost and effectiveness of using platinum(Pt)in them.The cathode catalyst layer(CL)is considered a core component in PEMFCs,and its composition often considerably affects the cell performance(V_(cell))also PEMFC fabrication and production(C_(stack))costs.In this study,a data-driven multi-objective optimization analysis is conducted to effectively evaluate the effects of various cathode CL compositions on Vcelland Cstack.Four essential cathode CL parameters,i.e.,platinum loading(L_(Pt)),weight ratio of ionomer to carbon(wt_(I/C)),weight ratio of Pt to carbon(wt_(Pt/c)),and porosity of cathode CL(ε_(cCL)),are considered as the design variables.The simulation results of a three-dimensional,multi-scale,two-phase comprehensive PEMFC model are used to train and test two famous surrogates:multi-layer perceptron(MLP)and response surface analysis(RSA).Their accuracies are verified using root mean square error and adjusted R^(2).MLP which outperforms RSA in terms of prediction capability is then linked to a multi-objective non-dominated sorting genetic algorithmⅡ.Compared to a typical PEMFC stack,the results of the optimal study show that the single-cell voltage,Vcellis improved by 28 m V for the same stack price and the stack cost evaluated through the U.S department of energy cost model is reduced by$5.86/k W for the same stack performance.
文摘The hepatitis B virus(HBV)is considered to be a major public health problem worldwide,and a significant number of reports on nosocomial outbreaks of HBV infections have been reported.Prevention of indirect HBV transmission by contaminated objects is only possible through the use of infection-control principles,including the use of chemical biocides,which are proven to render the virus non-infectious.The virucidal activity of biocides against HBV cannot be predicted;therefore,validation of the virucidal action of disinfectants against HBV is essential.However,feasible HBV infectivity assays have not yet been established.Thus,surrogate models have been proposed for testing the efficacy of biocides against HBV.Most of these assays do not correlate with HBV infectivity.Currently,the most promising and feasible assay is the use of the taxonomically related duck hepatitis B virus(DHBV),which belongs to the same Hepadnaviridae virus family.This paper reviews the application of DHBV,which can be propagated in vitro in primary duck embryonic hepatocytes,for the testing of biocides and describes why this model can be used as reliable method to evaluate disinfectants for efficacy against HBV.The susceptibility levels of important biocides,which are often used as ingredients for commercially available disinfectants,are also described.
基金Supported by the National Key Research and Development Program of China(2022YFB3904803)。
文摘The Infrared Hyperspectral Atmospheric SounderⅡ(HIRAS-Ⅱ)is the key equipment on FengYun-3E(FY-3E)satellite,which can realize vertical atmospheric detection,featuring hyper spectral,high sensitivity and high precision.To ensure its accuracy of detection,it is necessary to correlate their thermal models to in-orbit da⁃ta.In this work,an investigation of intelligent correlation method named Intelligent Correlation Platform for Ther⁃mal Model(ICP-TM)was established,the advanced Kriging surrogate model and efficient adaptive region opti⁃mization algorithm were introduced.After the correlation with this method for FY-3E/HIRAS-Ⅱ,the results indi⁃cate that compared with the data in orbit,the error of the thermal model has decreased from 5 K to within±1 K in cold case(10℃).Then,the correlated model is validated in hot case(20℃),and the correlated model exhibits good universality.This correlation precision is also much superiors to the general ones like 3 K in other similar lit⁃erature.Furthermore,the process is finished in 8 days using ICP-TM,the efficiency is much better than 3 months based on manual.The results show that the proposed approach significantly enhances the accuracy and efficiency of thermal model,this contributes to the precise thermal control of subsequent infrared optical payloads.
基金supported in part by a General Research Fund(grant number:17111414)Research Grants Council of Hong Kong+3 种基金Health and Medical Research Fund(grant numbers:HMRF 04151546)Food and Health Bureau,Government of the Hong Kong Special Administrative RegionShenzhen Science and Technology Program(KQTD20190929172749226)The University of Hong Kong-Shenzhen Hospital Fund for Shenzhen Key Medical Discipline(SZXK2020089)
文摘Successful embryo implantation requires highly coordinated maternal-embryo interactions.Implantation failure is a major factor contributing to infertility.However,the mechanism underlying implantation failure remains unclear.An improved understanding of the early implantation process not only improves the success rate of assisted reproductive treatments but also helps in studying the pathophysiology of reproductive disorders.Owing to ethical concerns,in vivo studies of human embryo implantation are not feasible.However,the results obtained from animal models cannot be directly applied to humans.Over the years,in vitro implantation models have been developed to investigate implantation mechanisms.In this review,we discuss the use of different models for generating embryo-like surrogates to study early embryo development and implantation in vitro,with a specific focus on stem cell-derived blastocyst-like embryo surrogates.There is no definitive evidence that the recently established embryo-like models re-capitulate all developmental events of human embryos during the peri-implantation stage.Regardless,stem cell-derived embryo surrogates are the most valuable tools for studying the mechanisms of early cell lineage differentiation and developmental failures during implantation.
基金National Natural Science Foundation of China for funding support via grant No 12175013the Interdisciplinary Research Project for Young Researchers of USTB and the Youth Teacher International Exchange&Growth Program of USTB(Fundamental Research Funds for the Central Universities,China)for funding support via grant No FRF-IDRY-21–018 and QNXM20250033,respectively.
文摘Evaluation of damage evolution effects in biodegradable pure Mg was carried out,using transmission electron microscope as surrogate irradiation for high-energy radionuclide β decay in Brachytherapy.Time-dependent quantitative defect production,evolution dynamics,and evolution statistics were revealed in-situ for two prism foils(z=[1.210],[10.10]),in as-received and heat-treated pure Mg,after 300 keV electron irradiation up to 0.468 dpa at R.T.Preferred nucleation of basal-plane interstitial-type 1/6<20.23>loops was confirmed,in addition to a small portion of prism-plane 1/3<11.20>loops.No cavities were found.A higher yield of point defect concentration and a more evident trend of defect coarsening were identified in[1.210]than in[10.10].Pre-existing dislocations(on the orders of 10^(13)−10^(14) m^(−2))in pure Mg resulted in a delay of the first occurrence of visible defects.Defect migration and elastic interactions governed the microstructural evolution of electron irradiation damage in pure Mg,giving rise to events of loop coalescence,growth,and sometimes rotation of habit plane.The influence of incident electron energy can be correlated to the rates of point defect production,and is quantifiable;however,interfered by defect cluster stability,defect mobility,and defect interactions.This forms an important theoretical basis for the application of Mg subjected to MeV-level β-decay radiation in Brachytherapy.The paper concludes with a brief comparison between Mg and conventional Ti casing,outlines the advantages and challenges,and provides reference points for the validation of Mg/Mg-alloys in Brachytherapy seed application.
基金supported by the National Natural Science Foundation of China(Nos.51775021,52302511)the Fundamental Research Funds for the Central Universities,China(Nos.YWF-23-JC-01,YWF-23-JC-04,YWF-23-JC-09)。
文摘Stratospheric airships are lighter-than-air vehicles capable of continuous flying for months.The energy balance of the airship is the key to long-duration flights.The stratospheric airship is entirely powered by the solar array.It is necessary to accurately predict the output power of the array for any flight state.Because of the uneven solar radiation received by the solar array,the traditional model based on components has a slow simulation speed.In this study,a data-driven surrogate modeling approach for prediction the output power of the solar array is proposed.The surrogate model is trained using the samples obtained from the high-accuracy simulation model.By using the input parameter preprocessor,the accuracy of the surrogate model in predicting the output power of the solar array is improved to 98.65%.In addition,the predictive speed of the surrogate model is ten million times faster than the traditional simulation model.Finally,the surrogate model is used to predict the energy balance of stratospheric airships flying throughout the year under actual global wind fields.
基金supported by the National Natural Science Foundation of China(Grant Nos.52425211,52272360,and 52472394)Chongqing Natural Science Foundation(CSTB2023NSCQ-MSX0300)。
文摘Trans-medium flight vehicles can combine high aerial maneuverability and underwater concealment ability,which have attracted much attention recently.As the most crucial procedure,the trajectory design generally determines the trans-medium flight vehicle performance.To quantitatively analyze the flight vehicle performance,an entire aerial-aquatic trajectory model is developed in this paper.Different from modeling a trajectory purely for the water entry process,the constructed entire trajectory model has integrated aerial,water entry,and underwater trajectories together,which can consider the influence of the connected trajectories.As for the aerial and underwater trajectories,explicit dynamic models are established to obtain the trajectory parameters.Due to the complicated fluid force during high-velocity water entry,a computational fluid dynamics model is investigated to analyze this phase.The compu-tational domain size is adaptively refined according to the final aerial trajectory state,where the redundant computational domain is removed.An entire trajectory optimization problem is then formulated to maximize the total flight range via tuning the joint states of different trajectories.Simultaneously,several constraints,i.e.,the max impact load,trajectory height,etc.,are involved in the optimization problem.Rather than directly optimizing by a heuristic algorithm,a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem.In this method,various surrogates coopera-tively generate infill sample points,thereby preventing the poor approximation.After optimization,the total flight range can be improved by 20%,while all the constraints are satisfied.The result demonstrates the effectiveness and practicability of the developed model and optimization framework.
基金funded by the CAMS Innovation Fund for Medical Sciences(CIFMS)(grant number:2024-I2M-C&T-B-071)the Beijing Hope Run Special Fund of Cancer Foundation of China(grant number:LC2018B04).
文摘Objective:A conventional endpoint for locally advanced cervical cancer(LACC)clinical trials is overall survival(OS)with five years of follow-up.The primary hypothesis was that progression-free survival(PFS)with three years of follow-up(PFS36)would be an appropriate primary surrogate endpoint.Materials and methods:The primary hypothesis,which was developed from our data,was further investigated using phase III randomized controlled trials and then externally validated using retrospective studies up to 2023.Correlation analysis at the treatment-arm level was performed between 2-,3-,4-,and 5-year PFS rates and 5-year OS.Results:A total of 613 patients with histologically confirmed cervical cancer who underwent radiotherapy or chemoradiation at our institute between January 2010 and December 2013 were eligible.The recurrence rates for years 1 through 5 were 12.9%,7.3%,3%,2.3%,and 1.8%,respectively.Patients who did not achieve PFS36 had a 5-year OS rate of 30.3%.However,patients who achieved PFS36 had a 5-year OS rate of 98.2%.Further data were extracted from 26 randomized phase III trials on LACC.The trials included 55 arms,with a pooled sample size of 7,281 patients.Trial-level surrogacy results revealed that PFS36(r2,0.732)was associated with 5-year OS.The correlation between PFS36 and OS was externally validated using independent retrospective data.Conclusion:A significant positive correlation was found between PFS36 and OS at 5 years of follow-up both within patients and across trials.These results suggest that PFS36 is an appropriate endpoint for LACC clinical trials of radiotherapy-based regimens.
文摘The authors regret that the original publication of this paper did not include Jawad Fayaz as a co-author.After further discussions and a thorough review of the research contributions,it was agreed that his significant contributions to the foundational aspects of the research warranted recognition,and he has now been added as a co-author.
基金Supported by the Major Scientific and Technological Special Project of CNPC(2023ZZ04)。
文摘The production optimization in the closed-loop reservoir management is generally empirical,and challenged by the issues such as low precision,low efficiency,and difficulty in solving constrained optimization problems.This paper outlines the main principles,advantages and disadvantages of commonly used production optimization methods/models,and then proposes an intelligent integrated production optimization method for waterflooding reservoirs that considers efficiency and precision,real-time and long-term effects,and the interaction and synergy between a variety of optimization models.This method integrates multiple optimization methods/models,such as reservoir performance analysis,reduced-physics models,and reservoir numerical models,with these model results and insights organically coupled to facilitate model construction and matching.This proposed method is elucidated and verified by field examples.The findings indicate that the optimal production optimization model varies depending on the specific application scenario.Reduced-physics models are conducive to short-term real-time optimization,whereas the simulator-based surrogate optimization and streamline-based simulation optimization methods are more suitable for long-term optimization strategy formulation,both of which need to be implemented under reasonable constraints from the perspective of reservoir engineering in order to be of practical value.
基金co-supported by the National Natural Science Foundation of China(No.52402460)project funded by the China Postdoctoral Science Foundation(No.2024T171113)supported by the Fundamental Research Funds for the Central Universities,China。
文摘This paper aims to design a morphing wing with both Flexible Leading Edge(FLE)and Flexible Trailing Edge(FTE)by using cellular structures,which can help the wing boost the deformation to a greater extent on the premise that the weight is not changed,so as to play a greater role in aerodynamic control such as gust interference.First,as for structural design,based on NACA0012,a morphing wing model constructed by 3 forms of cell structures is proposed.Then,the aerodynamic characteristics under the interference of FLE and FTE are calculated by the Computational Fluid Dynamic(CFD)method.After the surrogate model is established to predict the lift coefficient of the wing effectively,the sensitivity analysis reveals that the main sensitivity index of FTE deflection angle β is 0.565,which has the greatest influence on the lift coefficient.And the total sensitivity index of FLE deflection angle γ is increased by 78.9%,which reveals a strong coupling relationship between FLE and FTE.Finally,using Finite Element Analysis(FEA)method and experiment,the deformation capability of the model under certain static loads are obtained.The results reveal that the maximum deflection angle of the morphing wing model can be±22°at FLE and±64°at FTE,indicating strong structural stiffness and resistance to bending breakage of the model.The presented results can be useful in the design of the cellular morphing wing with multiple flexible systems.
基金the National Natural Science Foundation of China(No.52474068)the Major Collab-orative Innovation Project of Prospecting Breakthrough Stra-tegic Action in Guizhou Province(No.[2022]ZD001-003).
文摘Coalbed methane(CBM)is a vital unconventional energy resource,and predicting its spatiotemporal pressure dynamics is crucial for efficient development strategies.This paper proposes a novel deep learningebased data-driven surrogate model,AxialViT-ConvLSTM,which integrates AxialAttention Vision Transformer,ConvLSTM,and an enhanced loss function to predict pressure dynamics in CBM reservoirs.The results showed that the model achieves a mean square error of 0.003,a learned perceptual image patch similarity of 0.037,a structural similarity of 0.979,and an R^(2) of 0.982 between predictions and actual pressures,indicating excellent performance.The model also demonstrates strong robustness and accuracy in capturing spatialetemporal pressure features.
基金funding support from the National Natural Science Foundation of China(No.52204065,No.ZX20230398)supported by a grant from the Human Resources Development Program(No.20216110100070)of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)。
文摘In the realm of subsurface flow simulations,deep-learning-based surrogate models have emerged as a promising alternative to traditional simulation methods,especially in addressing complex optimization problems.However,a significant challenge lies in the necessity of numerous high-fidelity training simulations to construct these deep-learning models,which limits their application to field-scale problems.To overcome this limitation,we introduce a training procedure that leverages transfer learning with multi-fidelity training data to construct surrogate models efficiently.The procedure begins with the pre-training of the surrogate model using a relatively larger amount of data that can be efficiently generated from upscaled coarse-scale models.Subsequently,the model parameters are finetuned with a much smaller set of high-fidelity simulation data.For the cases considered in this study,this method leads to about a 75%reduction in total computational cost,in comparison with the traditional training approach,without any sacrifice of prediction accuracy.In addition,a dedicated well-control embedding model is introduced to the traditional U-Net architecture to improve the surrogate model's prediction accuracy,which is shown to be particularly effective when dealing with large-scale reservoir models under time-varying well control parameters.Comprehensive results and analyses are presented for the prediction of well rates,pressure and saturation states of a 3D synthetic reservoir system.Finally,the proposed procedure is applied to a field-scale production optimization problem.The trained surrogate model is shown to provide excellent generalization capabilities during the optimization process,in which the final optimized net-present-value is much higher than those from the training data ranges.
基金funding support from the National Natural Science Foundation of China (Nos. 42477208 and 52079134)the Natural Science Foundation of Hubei Province, China (No. 2024AFA072)+2 种基金the Youth Innovation Promotion Association CAS (No. 2022332)the National Key R&D Program of China (No. 2024YFF0508203)the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering Safety (Nos. SKLGME-JBGS2402 and SKLGME022022)。
文摘Accurate acquisition of the rock stress is crucial for various rock engineering applications.The hollow inclusion (HI) technique is widely used for measuring in-situ rock stress.This technique calculates the stress tensor by measuring strain using an HI strain cell.However,existing analytical solutions for stress calculation based on an HI strain cell in a double-layer medium are not applicable when an HI strain cell is used in a three-layer medium,leading to erroneous stress calculations.To address this issue,this paper presents a method for calculating stress tensors in a three-layer medium using numerical simulations,specifically by obtaining a constitutive matrix that relates strain measurements to stress tensors in a three-layer medium.Furthermore,using Latin hypercube sampling (LHS) and orthogonal experimental design strategies,764 groups of numerical models encompassing various stress measurement scenarios have been established and calculated using FLAC^(3D)software.Finally,a surrogate model based on artificial neural network (ANN) was developed to predict constitutive matrices,achieving a goodness of fit (R^(2)) of 0.999 and a mean squared error (MSE) of 1.254.A software program has been developed from this surrogate model for ease of use in practical engineering applications.The method’s accuracy was verified through numerical simulations,analytical solution and laboratory experiment,demonstrating its effectiveness in calculating stress in a three-layer medium.The surrogate model was applied to calculate mining-induced stress in the roadway roof rock of a coal mine,a typical case for stress measurement in a three-layer medium.Errors in stress calculations arising from the use of existing analytical solutions were corrected.The study also highlights the significant errors associated with using double-layer analytical solutions in a three-layer medium,which could lead to inappropriate engineering design.
文摘During high-speed forward flight,helicopter rotor blades operate across a wide range of Reynolds and Mach numbers.Under such conditions,their aerodynamic performance is significantly influenced by dynamic stall—a complex,unsteady flow phenomenon highly sensitive to inlet conditions such asMach and Reynolds numbers.The key features of three-dimensional blade stall can be effectively represented by the dynamic stall behavior of a pitching airfoil.In this study,we conduct an uncertainty quantification analysis of dynamic stall aerodynamics in high-Mach-number flows over pitching airfoils,accounting for uncertainties in inlet parameters.A computational fluid dynamics(CFD)model based on the compressible unsteady Reynolds-averagedNavier–Stokes(URANS)equations,coupledwith sliding mesh techniques,is developed to simulate the unsteady aerodynamic behavior and associated flow fields.To efficiently capture the aerodynamic responses while maintaining high accuracy,a multi-fidelity Co-Kriging surrogate model is constructed.This model integrates the precision of high-fidelity wind tunnel experiments with the computational efficiency of lower-fidelity URANS simulations.Its accuracy is validated through direct comparison with experimental data.Building upon this surrogate model,we employ interval analysis and the Sobol sensitivity method to quantify the uncertainty and parameter sensitivity of the unsteady aerodynamic forces resulting frominlet condition variability.Both the inlet Mach number and Reynolds number are treated as uncertain inputs,modeled using interval representations.Our results demonstrate that variations inMach number contribute far more significantly to aerodynamic uncertainty than those in Reynolds number.Moreover,the presence of dynamic stall vortices markedly amplifies the aerodynamic sensitivity to Mach number fluctuations.
基金supported by the National Natural Science Foundation of China(Grant No.41961134032).
文摘The surrogate model serves as an efficient simulation tool during the slope parameter inversion process.However,the creep constitutive model integrated with dynamic damage evolution poses challenges in development of the required surrogate model.In this study,a novel physics knowledge-based surrogate model framework is proposed.In this framework,a Transformer module is employed to capture straindriven softening-hardening physical mechanisms.Positional encoding and self-attention are utilized to transform the constitutive parameters associated with shear strain,which are not directly time-related,into intermediate latent features for physical loss calculation.Next,a multi-layer stacked GRU(gated recurrent unit)network is built to provide input interfaces for time-dependent intermediate latent features,hydraulic boundary conditions,and water-rock interaction degradation equations,with static parameters introduced via external fully-connected layers.Finally,a combined loss function is constructed to facilitate the collaborative training of physical and data loss,introducing time-dependent weight adjustments to focus the surrogate model on accurate deformation predictions during critical phases.Based on the deformation of a reservoir bank landslide triggered by impoundment and subsequent restabilization,an elasto-viscoplastic constitutive model that considers water effect and sliding state dependencies is developed to validate the proposed surrogate model framework.The results indicate that the framework exhibits good performance in capturing physical mechanisms and predicting creep behavior,reducing errors by about 30 times compared to baseline models such as GRU and LSTM(long short-term memory),meeting the precision requirements for parameter inversion.Ablation experiments also confirmed the effectiveness of the framework.This framework can also serve as a reference for constructing other creep surrogate models that involve non-time-related across dimensions.
基金supported by the Basic Public Welfare Research Program of Zhejiang Province(No.LGN22E050005).
文摘This study proposes a multi-objective optimization framework for electric winches in fiber-reinforced plastic(FRP)fishing vessels to address critical limitations of conventional designs,including excessive weight,material inefficiency,and performance redundancy.By integrating surrogate modeling techniques with a multi-objective genetic algorithm(MOGA),we have developed a systematic approach that encompasses parametric modeling,finite element analysis under extreme operational conditions,and multi-fidelity performance evaluation.Through a 10-t electric winch case study,the methodology’s effectiveness is demonstrated via parametric characterization of structural integrity,stiffness behavior,and mass distribution.The comparative analysis identified optimal surrogate models for predicting key performance metrics,which enabled the construction of a robust multi-objective optimization model.The MOGA-derived Pareto solutions produced a design configuration achieving 7.86%mass reduction,2.01%safety factor improvement,and 23.97%deformation mitigation.Verification analysis confirmed the optimization scheme’s reliability in balancing conflicting design requirements.This research establishes a generalized framework for marine deck machinery modernization,particularly addressing the structural compatibility challenges in FRP vessel retrofitting.The proposed methodology demonstrates significant potential for facilitating sustainable upgrades of fishing vessel equipment through systematic performance optimization.
基金supported by the National Key Research and Development Program of China(No.2023YFB4604800)the National Natural Science Foundation of China(No.52075195)the Inelligent Manufacturing Equipment and Technology Open Foundation(No.IMETKF2023016).
文摘Simultaneously,reducing an acoustic metamaterial’s weight and sound pressure level is an important but difficult topic.Considering the law of mass,traditional lightweight acoustic metamaterials make it difficult to control noise efficiently in real-life applications.In this study,a novel optimization-driven design scheme is developed to obtain lightweight acoustic metamaterials with a strong sound insulation capability for additive manufacturing.In the proposed design scheme,a topology optimization method for an acoustic metamaterial in the acoustic-solid interaction system is implemented to obtain an initial cross-sectional topology of the acoustic microstructure during the conceptual design phase.Then,in the detailed design phase,the parametric model for a higher-dimensional design is formulated based on the topology optimization result.An adaptive Kriging interpolation approach is proposed to accurately reformulate a much easier surrogate model from the original parameterization formulation to avoid repeating calls for nonlinear analyses in the 3D acoustic-structure interaction system.A surrogate model was used to optimize a ready-to-print acoustic metamaterial with improved noise reduction performance.Experimental verification based on an impedance tube is implemented.Results demonstrate characteristics of the devised metamaterial as well as the proposed method.
文摘The rapid development of evolutionary deep learning has led to the emergence of various Neural Architecture Search(NAS)algorithms designed to optimize neural network structures.However,these algorithms often face significant computational costs due to the time-consuming process of training neural networks and evaluating their performance.Traditional NAS approaches,which rely on exhaustive evaluations and large training datasets,are inefficient for solving complex image classification tasks within limited time frames.To address these challenges,this paper proposes a novel NAS algorithm that integrates a hierarchical evaluation strategy based on Surrogate models,specifically using supernet to pre-trainweights and randomforests as performance predictors.This hierarchical framework combines rapid Surrogate model evaluations with traditional,precise evaluations to balance the trade-off between performance accuracy and computational efficiency.The algorithm significantly reduces the time required for model evaluation by predicting the fitness of candidate architectures using a random forest Surrogate model,thus alleviating the need for full training cycles for each architecture.The proposed method also incorporates evolutionary operations such as mutation and crossover to refine the search process and improve the accuracy of the resulting architectures.Experimental evaluations on the CIFAR-10 and CIFAR-100 datasets demonstrate that the proposed hierarchical evaluation strategy reduces the search time and costs compared to traditional methods,while achieving comparable or even superior model performance.The results suggest that this approach can efficiently handle resourceconstrained tasks,providing a promising solution for accelerating the NAS process without compromising the quality of the generated architectures.
文摘Low collateral damage weapons achieve controlled personnel injury through the coupling of shock waves and particle swarms,where the particle swarms arise from the high-explosive dispersion of compacted metal particle ring.To investigate the dynamic response of the human target under combined shock waves and particle swarms loading,a physical human surrogate torso model(HSTM)was developed,and the dynamic response test experiment was conducted under the combined loading.The effects of particle size on the loading parameters,the damage patterns of the ballistic plate and HSTM,and the dynamic response parameters of the HSTM with and without protection are mainly analyzed.Our findings revealed that particle swarms can effectively delay the shock wave attenuation,especially the best effect when the particle size was 0.28–0.45 mm.The ballistic plate mainly exhibited dense perforation of the outer fabric and impacted crater damage of ceramic plates,whereas the unprotected HSTM was mainly dominated by high-density and small-size ballistic cavity group damage.The peak values of the dynamic response parameters for the HSTM under combined loading were significantly larger than those under bare charge loading,with multiple peaks observed.Under unprotected conditions,the peak acceleration of skeletons and peak pressure of organs increased with the particle size.Under protected conditions,the particle size,the number of particles hit,and the fit of the ballistic plate to the HSTM together affected the dynamic response parameters of the HSTM.
