For a degradable structural system with fuzzy failure region, a moment method based on fuzzy reliability sensitivity algorithm is presented. According to the value assignment of performance function, the integral regi...For a degradable structural system with fuzzy failure region, a moment method based on fuzzy reliability sensitivity algorithm is presented. According to the value assignment of performance function, the integral region for calculating the fuzzy failure probability is first split into a series of subregions in which the membership function values of the performance function within the fuzzy failure region can be approximated by a set of constants. The fuzzy failure probability is then transformed into a sum of products of the random failure probabilities and the approximate constants of the membership function in the subregions. Furthermore, the fuzzy reliability sensitivity analysis is transformed into a series of random reliability sensitivity analysis, and the random reliability sensitivity can be obtained by the constructed moment method. The primary advantages of the presented method include higher efficiency for implicit performance function with low and medium dimensionality and wide applicability to multiple failure modes and nonnormal basic random variables. The limitation is that the required computation effort grows exponentially with the increase of dimensionality of the basic random vari- able; hence, it is not suitable for high dimensionality problem. Compared with the available methods, the presented one is pretty competitive in the case that the dimensionality is lower than 10. The presented examples are used to verify the advantages and indicate the limitations.展开更多
Saline aquifers are considered as highly favored reservoirs for CO_(2)sequestration due to their favorable properties.Understanding the impact of saline aquifer properties on the migration and distribution of CO_(2)pl...Saline aquifers are considered as highly favored reservoirs for CO_(2)sequestration due to their favorable properties.Understanding the impact of saline aquifer properties on the migration and distribution of CO_(2)plume is crucial.This study focuses on four key parameters-permeability,porosity,formation pressure,and temperature-to characterize the reservoir and analyse the petrophysical and elastic response of CO_(2).First,we performed reservoir simulations to simulate CO_(2)saturation,using multiple sets of these four parameters to examine their significance on CO_(2)saturation and the plume migration speed.Subsequently,the effect of these parameters on the elastic properties is tested using rock physics theory.We established a relationship of compressional wave velocity(V_(p))and quality factor(Q_(p))with the four key parameters,and conducted a sensitivity analysis to test their sensitivity to V_(p) and Q_(p).Finally,we utilized visco-acoustic wave equation simulated time-lapse seismic data based on the computed V_(p) and Q_(p) models,and analysed the impact of CO_(2) saturation changes on seismic data.As for the above nu-merical simulations and analysis,we conducted sensitivity analysis using both homogeneous and heterogeneous models.Consistent results are found between homogeneous and heterogeneous models.The permeability is the most sensitive parameter to the CO_(2)saturation,while porosity emerges as the primary factor affecting both Q_(p) and V_(p).Both Q_(p) and V_(p) increase with the porosity,which contradicts the observations in gas reservoirs.The seismic simulations highlight significant variations in the seismic response to different parameters.We provided analysis for these observations,which serves as a valuable reference for comprehensive CO_(2)integrity analysis,time-lapse monitoring,injection planning and site selection.展开更多
As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal vari...As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.展开更多
Accurate quantification of carbon and water fluxes dynamics in arid and semi-arid ecosystems is a critical scientific challenge for regional carbon neutrality assessments and sustainable water resource management.In t...Accurate quantification of carbon and water fluxes dynamics in arid and semi-arid ecosystems is a critical scientific challenge for regional carbon neutrality assessments and sustainable water resource management.In this study,we developed a multi-flux global sensitivity discriminant index(D_(sen))by integrating the Biome-BGCMuSo model with eddy covariance flux observations.This index was combined with a Bayesian optimization algorithm to conduct parameter optimization.The results demonstrated that:(1)Sensitivity analysis identified 13 highly sensitive parameters affecting carbon and water fluxes.Among these,the canopy light extinction coefficient(k)and the fraction of leaf N in Rubisco(FLNR)exhibited significantly higher sensitivity to carbon fluxes(GPP,NEE,Reco;D_(sen)>10%)compared to water flux(ET).This highlights the strong dependence of carbon cycle simulations on vegetation physiological parameters.(2)The Bayesian optimization framework efficiently converged 30 parameter spaces within 50 iterations,markedly improving carbon fluxes simulation accuracy.The Kling-Gupta efficiency(KGE)values for Gross Primary Production(GPP),Net Ecosystem Exchange(NEE),and Total Respiration(Reco)increased by 44.94%,69.23%and 123%,respectively.The optimization prioritized highly sensitive parameters,underscoring the necessity of parameter sensitivity stratification.(3)The optimized model effectively reproduced carbon sink characteristics in mountain meadows during the growing season(cumulative NEE=-375 g C/m^(2)).It revealed synergistic carbon-water fluxes interactions governed by coupled photosynthesis-stomatal pathways and identified substrate supply limitations on heterotrophic respiration.This study proposes a novel multi-flux sensitivity index and an efficient optimization framework,elucidating the coupling mechanisms between vegetation physiological regulation(k,FLNR)and environmental stressors(VPD,SWD)in carbonwater cycles.The methodology offers a practical approach for arid ecosystem model optimization and provides theoretical insights for grassland management through canopy structure regulation and water-use efficiency enhancement.展开更多
In engineering systems,uncertainties in input parameters can significantly influence the output responses.This paper proposes a model distance-based approach to perform global sensitivity analysis for quantifying the ...In engineering systems,uncertainties in input parameters can significantly influence the output responses.This paper proposes a model distance-based approach to perform global sensitivity analysis for quantifying the influence of input uncertainties on multiple responses in an engineering system.The sensitivity indices are determined by comparing a reference model that incorporates all system uncertainties,with an altered model,where specific uncertainties are constrained.The proposed framework employs probability distance measures such as Hellinger distance,Kullback-Leibler divergence,and I2 norm which are based on joint probability density functions.The study also demonstrates the equivalence between the l2 norm-based approach and Sobol's analysis in multivariate sensitivity context.The proposed methodology effectively manages correlated random variables,accommodates both Gaussian and non-Gaussian distributions,and allows for the grouping of input variables.Ilustrative examples consist of static analysis of a truss system and dynamic analysis of a frame subjected to seismic excitation.The sensitivity indices are estimated using brute-force Monte Carlo simulations.The relative ranking of these sensitivity indices can be utilized to identify the most and least significant variables contributing to the response uncertainty.The numerical results show a consistent ranking of input variables across different probability measures,indicating the robustness of proposed framework.展开更多
This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-...This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-oped using the material point method.To reduce the computational cost of Monte Carlo simulations,response surface models are created as surrogate models for the material point system to approximate its dynamic behavior.An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order,effectively balancing the accuracy and computational efficiency of the surrogate model.Based on the sparse polynomial chaos expansion,sensitivity analysis is conducted using the global finite difference and Sobol methods.Several examples of structural dynamics are provided to demonstrate the effectiveness of the proposed method in addressing structural dynamics problems.展开更多
Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting ...Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting multi-hazard dynamic responses to super high-rise structures has significant engineering and scientific value. This study performed a parametric global sensitivity analysis (GSA) for multi-hazard dynamic response prediction of super high-rise structures using the multiple-degree-of-freedom shear (MFS) model. Polynomial chaos Kriging (PCK) was introduced to build a surrogate model that allowed GSA to be combined with Sobol’ indices. Monte Carlo simulation (MCS) is also conducted for the comparison to verify the accuracy and efficiency of the PCK method. Parametric sensitivity analysis is performed for a wide range of aleatory uncertainty (intensities of coupled multi-hazard), epistemic uncertainty (bending stiffness, k_(m);shear stiffness, kq;density, ρ;and damping ratio, ξ), probability distribution types, and coefficients of variation. The results indicate that epistemic uncertainty parameters, k_(m), ρ, and ξ dramatically affect the multi-hazard dynamic responses of super high-rise structures;in addition, Sobol’ indices between the normal and lognormal distributions are insignificant, while the variation levels have remarkably influenced the sensitivity indices.展开更多
While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensificati...While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensification(RI),whose nonlinear characteristics impose great difficulties for numerical models.The ensemble sensitivity analysis(ESA)method is used here to analyze the initial conditions that contribute to typhoon intensity forecasts,especially with RI.Six RI processes from five typhoons(Chaba,Haima,Meranti,Sarika,and Songda)in 2016,are applied with ESA,which also gives a composite initial condition that favors subsequent RI.Results from individual cases have generally similar patterns of ESA,but with different magnitudes,when various cumulus parameterization schemes are applied.To draw the initial conditions with statistical significance,sample-mean azimuthal components of ESA are obtained.Results of the composite sensitivity show that typhoons that experience RI in 24 h favor enhanced primary circulation from low to high levels,intensified secondary circulation with increased radial inflow at lower levels and increased radial outflow at upper levels,a prominent warm core at around 300 hPa,and increased humidity at low levels.As the forecast lead time increases,the patterns of ESA are retained,while the sensitivity magnitudes decay.Given the general and quantitative composite sensitivity along with associated uncertainties for different cumulus parameterization schemes,appropriate sampling of the composite sensitivity in numerical models could be beneficial to capturing the RI and improving the forecasting of typhoon intensity.展开更多
In recent years,incidents of simultaneous exceedance of PM_(2.5)and O_(3) concentrations,termed PM_(2.5)and O_(3) co-pollution events,have frequently occurred in China.This study conducted atmospheric circulation anal...In recent years,incidents of simultaneous exceedance of PM_(2.5)and O_(3) concentrations,termed PM_(2.5)and O_(3) co-pollution events,have frequently occurred in China.This study conducted atmospheric circulation analysis on two typical co-pollution events in Beijing,occurring from July 22 to July 28,2019,and from April 25 to May 2,2020.These events were categorized into pre-trough southerly airflow type(Type 1)and post-trough northwest flow type(Type 2).Subsequently,sensitivity analyses using the GRAPES-CUACE adjoint model were performed to quantify the contributions of precursor emissions from Beijing and surrounding areas to PM_(2.5)and O_(3) concentrations in Beijing for two types of co-pollution.The results indicated that the spatiotemporal distribution of sensitive source region varied among different circulation types.Primary PM_(2.5)(PPM_(2.5))emissions from Hebei contributed the most to the 24-hour average PM_(2.5)(24-h PM_(2.5))peak concentration(41.6%-45.4%),followed by Beijing emissions(31%-35.7%).The maximum daily 8-hour average ozone peak concentration was primarily influenced by the emissions from Hebei and Beijing,with contribution ratios respectively of 32.8%-44.8% and 29%-42.1%.Additionally,NO_(x)emissions were the main contributors in Type 1,while both NO_(x)and VOCs emissions contributed similarly in Type 2.The iterative emission reduction experiments for two types of co-pollution indicated that Type 1 required emission reductions in NO_(x)(52.4%-71.8%)and VOCs(14.1%-33.8%)only.In contrast,Type 2 required combined emission reductions in NO_(x)(37.0%-65.1%),VOCs(30.7%-56.2%),and PPM_(2.5)(31%-46.9%).This study provided a reference for controlling co-pollution events and improving air quality in Beijing.展开更多
The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for...The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for modelling urban growth to closely reflects reality.Despite extensive research,ambiguity remains about how variations in these input variables influence urban densification.In this study,we conduct a global sensitivity analysis(SA)using a multinomial logistic regression(MNL)model to assess the model’s explanatory and predictive power.We examine the influence of global variables,including spatial resolution,neighborhood size,and density classes,under different input combinations at a provincial scale to understand their impact on densification.Additionally,we perform a stepwise regression to identify the significant explanatory variables that are important for understanding densification in the Brussels Metropolitan Area(BMA).Our results indicate that a finer spatial resolution of 50 m and 100 m,smaller neighborhood size of 5×5 and 3×3,and specific density classes—namely 3(non-built-up,low and high built-up)and 4(non-built-up,low,medium and high built-up)—optimally explain and predict urban densification.In line with the same,the stepwise regression reveals that models with a coarser resolution of 300 m lack significant variables,reflecting a lower explanatory power for densification.This approach aids in identifying optimal and significant global variables with higher explanatory power for understanding and predicting urban densification.Furthermore,these findings are reproducible in a global urban context,offering valuable insights for planners,modelers and geographers in managing future urban growth and minimizing modelling.展开更多
Kangbao County is located in the northwest of Bashang in Hebei Province,which is a sub-arid area in the middle temperate zone,with a cold and arid climate and frequent disastrous weather.The meteorological data of Kan...Kangbao County is located in the northwest of Bashang in Hebei Province,which is a sub-arid area in the middle temperate zone,with a cold and arid climate and frequent disastrous weather.The meteorological data of Kangbao County Meteorological Station from 1994 to 2023 were selected,and the meteorological elements such as air pressure,temperature,precipitation,wind,relative humidity,sunshine,thunderstorm,hail,gale,rainstorm,fog,and snow cover were counted.The climate background analysis and high-impact weather analysis were carried out in combination with the topographic characteristics,geographical location,and climate characteristics.The results of meteorological sensitivity survey in the park showed that industries such as food,agriculture and new energy are very sensitive to temperature.During the visit to the enterprises in the park,it was found that heavy precipitation,snow,strong winds and hail had a great impact on many industries,and it was recommended to carry out long-term planning and reasonable design of buildings.It should pay close attention to forecasts and early warnings,formulate emergency plans for high-impact weather defense,and actively take preventive measures.展开更多
This paper puts forward a rigorous approach for a sensitivity analysis of stochastic user equilibrium with the elastic demand （SUEED） model. First, proof is given for the existence of derivatives of output variables...This paper puts forward a rigorous approach for a sensitivity analysis of stochastic user equilibrium with the elastic demand （SUEED） model. First, proof is given for the existence of derivatives of output variables with respect to the perturbation parameters for the SUEED model. Then by taking advantage of the gradient-based method for sensitivity analysis of a general nonlinear program, detailed formulae are developed for calculating the derivatives of designed variables with respect to perturbation parameters at the equilibrium state of the SUEED model. This method is not only applicable for a sensitivity analysis of the logit-type SUEED problem, but also for the probit-type SUEED problem. The application of the proposed method in a numerical example shows that the proposed method can be used to approximate the equilibrium link flow solutions for both logit-type SUEED and probit-type SUEED problems when small perturbations are introduced in the input parameters.展开更多
Parallel kinematic machines （PKMs） have the advantages of a compact structure,high stiffness,a low moving inertia,and a high load/weight ratio.PKMs have been intensively studied since the 1980s,and are still attract...Parallel kinematic machines （PKMs） have the advantages of a compact structure,high stiffness,a low moving inertia,and a high load/weight ratio.PKMs have been intensively studied since the 1980s,and are still attracting much attention.Compared with extensive researches focus on their type/dimensional synthesis,kinematic/dynamic analyses,the error modeling and separation issues in PKMs are not studied adequately,which is one of the most important obstacles in its commercial applications widely.Taking a 3-PRS parallel manipulator as an example,this paper presents a separation method of source errors for 3-DOF parallel manipulator into the compensable and non-compensable errors effectively.The kinematic analysis of 3-PRS parallel manipulator leads to its six-dimension Jacobian matrix,which can be mapped into the Jacobian matrix of actuations and constraints,and then the compensable and non-compensable errors can be separated accordingly.The compensable errors can be compensated by the kinematic calibration,while the non-compensable errors may be adjusted by the manufacturing and assembling process.Followed by the influence of the latter,i.e.,the non-compensable errors,on the pose error of the moving platform through the sensitivity analysis with the aid of the Monte-Carlo method,meanwhile,the configurations of the manipulator are sought as the pose errors of the moving platform approaching their maximum.The compensable and non-compensable errors in limited-DOF parallel manipulators can be separated effectively by means of the Jacobian matrix of actuations and constraints,providing designers with an informative guideline to taking proper measures for enhancing the pose accuracy via component tolerancing and/or kinematic calibration,which can lay the foundation for the error distinguishment and compensation.展开更多
Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parall...Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.展开更多
The previous sensitivity analysis researches are not accurate enough and also have the limited reference value, because those mathematical models are relatively simple and the change of the load and the initial displa...The previous sensitivity analysis researches are not accurate enough and also have the limited reference value, because those mathematical models are relatively simple and the change of the load and the initial displacement changes of the piston are ignored, even experiment verification is not conducted. Therefore, in view of deficiencies above, a nonlinear mathematical model is established in this paper, including dynamic characteristics of servo valve, nonlinear characteristics of pressure-flow, initial displacement of servo cylinder piston and friction nonlinearity. The transfer function block diagram is built for the hydraulic drive unit closed loop position control, as well as the state equations. Through deriving the time-varying coefficient items matrix and time-varying free items matrix of sensitivity equations respectively, the expression of sensitivity equations based on the nonlinear mathematical model are obtained. According to structure parameters of hydraulic drive unit, working parameters, fluid transmission characteristics and measured friction-velocity curves, the simulation analysis of hydraulic drive unit is completed on the MATLAB/Simulink simulation platform with the displacement step 2 mm, 5 mm and 10 mm, respectively. The simulation results indicate that the developed nonlinear mathematical model is sufficient by comparing the characteristic curves of experimental step response and simulation step response under different constant load. Then, the sensitivity function time-history curves of seventeen parameters are obtained, basing on each state vector time-history curve of step response characteristic. The maximum value of displacement variation percentage and the sum of displacement variation absolute values in the sampling time are both taken as sensitivity indexes. The sensitivity indexes values above are calculated and shown visually in histograms under different working conditions, and change rules are analyzed. Then the sensitivity indexes values of four measurable parameters, such as supply pressure, proportional gain, initial position of servo cylinder piston and load force, are verified experimentally on test platform of hydraulic drive unit, and the experimental research shows that the sensitivity analysis results obtained through simulation are approximate to the test results. This research indicates each parameter sensitivity characteristics of hydraulic drive unit, the performance-affected main parameters and secondary parameters are got under different working conditions, which will provide the theoretical foundation for the control compensation and structure optimization of hydraulic drive unit.展开更多
Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bott...Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bottle-neck to achieve parameters optimization. For this reason, a new approach was proposed in this paper, in which the support vector machine was used to construct the response surface at first. Then it integrates the SVM-based response surface with the Sobol＇ method, i.e. the RSMSoboI＇ method, to quantify the parameter sensi- tivities. In this work, the distributed time-variant gain model （DTVGM） was applied to the Huaihe River Basin, which was used as a case to verify its validity and feasibility. We selected three objective functions （i.e. water balance coefficient WB, Nash-Sutcliffe efficiency coefficient NS, and correlation coefficient RC） to assess the model performance as the output responses for sensitivity analysis. The results show that the parameters gl and g2 are most important for all the objective functions, and they are almost the same to that of the classical approach. Furthermore, the RSMSobol method can not only achieve the quantification of the sensitivity, and also reduce the computational cost, with good accuracy compared to the classical approach. And this approach will be effective and reliable in the global sensitivity analysis for a complex modelling system.展开更多
The mechanical properties of cemented paste backfill(CPB) depend heavily on its pore structural characteristics and micro-structural changes. In order to explore the variation mechanisms of macro-mechanical characteri...The mechanical properties of cemented paste backfill(CPB) depend heavily on its pore structural characteristics and micro-structural changes. In order to explore the variation mechanisms of macro-mechanical characteristics and micro-structure of CPB. CPB specimens with different mass concentrations prepared from the full tailings of Xianglushan Tungsten Ore were micro-tests. Moreover, acquired pore digital images were processed by using the pores(particles) and cracks analysis system(PCAS), and a sensitivity analysis was performed. The results show that as the mass concentration of CPB increases from 70% to 78%, the porosity, the average pore area and the number of pores drop overall, leading to a decline in the pores opening degree and enhancing the mechanical characteristics. As the mass concentration of CPB increases, the trend of fractal dimension, probability entropy and roundness is reduced, constant and increased, which can result in an enhancement of the uniformity, an unchanged directionality and more round pores. According to the definition of sensitivity, the sensitivities of various micro-parameters were calculated and can be ranked as porosity > average pore area > number of pores > roundness > fractal dimension > probability entropy.展开更多
In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on p...In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on physical model and sensitivity analysis. Firstly, a physical model of tooth damage and mesh stiffness is built. Secondly, some effective condition indicators （Cls） are presented, and the optimal Cls set is selected by comparing their test statistics according to Mann-Kendall test. Afterwards, the selected CIs are used to generate a health indicator （HI） through sen slop estimator. Then, the sensors are selected according to the monotonic relevance and sensitivity to the damage levels. Finally, the proposed method is verified by the simulation and experimental data. The results show that the approach can provide a guide for health monitor- ing of helicopter transmission systems, and it is effective to reduce the test cost and improve the system＇s reliability.展开更多
This paper presents an application of global sensitivity analysis for system safety analysis of reciprocating aircraft engine. Compared with local sensitivity analysis results, global sensitivity analysis could provid...This paper presents an application of global sensitivity analysis for system safety analysis of reciprocating aircraft engine. Compared with local sensitivity analysis results, global sensitivity analysis could provide more information on parameter inter- actions, which are significant in complex system safety analysis. First, a deterministic aviation reciprocating engine thermody- namics model is developed and parameters of interest are defined as random variables. Then, samples are generated by Monte Carlo method for the parameters used in engine model on the basis of definition of factor distribution. Eventually, results from engine model are generated and importance indices are calculated. Based on the analysis results, design is improved to satisfy the airworthiness requirements. The results reveal that by using global sensitivity analysis, the parameters could be ranked with respect to their importance, including first order indices and total sensitivity indices. By reducing the uncertainty of parameters and adjusting the range of inputs, safety criteria would be satisfied.展开更多
Natural laminar flow technology can significantly reduce aircraft aerodynamic drag and has excellent technical appeal for transport aircraft development with high aerodynamic efficiency.Accurately and efficiently pred...Natural laminar flow technology can significantly reduce aircraft aerodynamic drag and has excellent technical appeal for transport aircraft development with high aerodynamic efficiency.Accurately and efficiently predicting the laminar-to-turbulent transition and revealing the maintenance mechanism of laminar flow in a transport aircraft’s flight environment are significant for developing natural laminar flow wings.In this research,we carry out natural laminar flow flight experiments with different Reynolds numbers and angles of attack.The critical N-factor is calibrated as 9.0 using flight experimental data and linear stability theory from a statistical perspective,which makes sure that the relative error of transition location is within 5%.We then implement a simplified e^(N) transition prediction method with a similar accuracy compared with linear stability theory.We compute the sensitivity information for the simplified eN method with an adjointbased method,using the automatic differentiation technique(ADjoint).The impact of Reynolds numbers and pressure distributions on TS waves is analyzed using the sensitivity information.Through the sensitivity analysis,we find that:favorable pressure gradients not only suppress the development of TS waves but also decrease their sensitivity to Reynolds numbers;there exist three special regions which are very sensitive to the pressure distribution,and the sensitivity decreases as the local favorable pressure gradient increases.The proposed sensitivity analysis method enables robust natural laminar flow wings design.展开更多
基金Foundation items： National Natural Science Foundation of China （NSFC 10572117） National High-tech Research and Development Program （2007AA04Z401）+1 种基金 New Century Program for Excellent Talents of Ministry of Education of China （NCET-05-0868） Aeronautical Science Foundation of China （2007ZA53012）
文摘For a degradable structural system with fuzzy failure region, a moment method based on fuzzy reliability sensitivity algorithm is presented. According to the value assignment of performance function, the integral region for calculating the fuzzy failure probability is first split into a series of subregions in which the membership function values of the performance function within the fuzzy failure region can be approximated by a set of constants. The fuzzy failure probability is then transformed into a sum of products of the random failure probabilities and the approximate constants of the membership function in the subregions. Furthermore, the fuzzy reliability sensitivity analysis is transformed into a series of random reliability sensitivity analysis, and the random reliability sensitivity can be obtained by the constructed moment method. The primary advantages of the presented method include higher efficiency for implicit performance function with low and medium dimensionality and wide applicability to multiple failure modes and nonnormal basic random variables. The limitation is that the required computation effort grows exponentially with the increase of dimensionality of the basic random vari- able; hence, it is not suitable for high dimensionality problem. Compared with the available methods, the presented one is pretty competitive in the case that the dimensionality is lower than 10. The presented examples are used to verify the advantages and indicate the limitations.
基金supported by the State Key Laboratory of Offshore Oil and Gas Exploitation, Open Fund Project (No. CCL2023RCPS0162RQN)the primary funding, National Natural Science Foundation of China (No. ZX20230400)
文摘Saline aquifers are considered as highly favored reservoirs for CO_(2)sequestration due to their favorable properties.Understanding the impact of saline aquifer properties on the migration and distribution of CO_(2)plume is crucial.This study focuses on four key parameters-permeability,porosity,formation pressure,and temperature-to characterize the reservoir and analyse the petrophysical and elastic response of CO_(2).First,we performed reservoir simulations to simulate CO_(2)saturation,using multiple sets of these four parameters to examine their significance on CO_(2)saturation and the plume migration speed.Subsequently,the effect of these parameters on the elastic properties is tested using rock physics theory.We established a relationship of compressional wave velocity(V_(p))and quality factor(Q_(p))with the four key parameters,and conducted a sensitivity analysis to test their sensitivity to V_(p) and Q_(p).Finally,we utilized visco-acoustic wave equation simulated time-lapse seismic data based on the computed V_(p) and Q_(p) models,and analysed the impact of CO_(2) saturation changes on seismic data.As for the above nu-merical simulations and analysis,we conducted sensitivity analysis using both homogeneous and heterogeneous models.Consistent results are found between homogeneous and heterogeneous models.The permeability is the most sensitive parameter to the CO_(2)saturation,while porosity emerges as the primary factor affecting both Q_(p) and V_(p).Both Q_(p) and V_(p) increase with the porosity,which contradicts the observations in gas reservoirs.The seismic simulations highlight significant variations in the seismic response to different parameters.We provided analysis for these observations,which serves as a valuable reference for comprehensive CO_(2)integrity analysis,time-lapse monitoring,injection planning and site selection.
基金supported by the National Natural Science Foundation of China(Grant Nos.42250103 and 42174090)the Opening Fund of Key Laboratory of Geological Survey and Evaluation of Ministry of Education(Grant No.GLAB2023ZR02)the Ministry of Science and Technology(MOST)Special Fund from the State Key Laboratory of Geological Processes and Mineral Resources(Grant No.MSFGPMR2022-4)。
文摘As a means of quantitative interpretation,forward calculations of the global lithospheric magnetic field in the Spherical Harmonic(SH)domain have been widely used to reveal geophysical,lithological,and geothermal variations in the lithosphere.Traditional approaches either do not consider the non-axial dipolar terms of the inducing field and its radial variation or do so by means of complicated formulae.Moreover,existing methods treat the magnetic lithosphere either as an infinitesimally thin layer or as a radially uniform spherical shell of constant thickness.Here,we present alternative forward formulae that account for an arbitrarily high maximum degree of the inducing field and for a magnetic lithosphere of variable thickness.Our simulations based on these formulae suggest that the satellite magnetic anomaly field is sensitive to the non-axial dipolar terms of the inducing field but not to its radial variation.Therefore,in forward and inverse calculations of satellite magnetic anomaly data,the non-axial dipolar terms of the inducing field should not be ignored.Furthermore,our results show that the satellite magnetic anomaly field is sensitive to variability in the lateral thickness of the magnetized shell.In particular,we show that for a given vertically integrated susceptibility distribution,underestimating the thickness of the magnetic layer overestimates the induced magnetic field.This discovery bridges the greatest part of the alleged gap between the susceptibility values measured from rock samples and the susceptibility values required to match the observed magnetic field signal.We expect the formulae and conclusions of this study to be a valuable tool for the quantitative interpretation of the Earth's global lithospheric magnetic field,through an inverse or forward modelling approach.
基金jointly funded by the National Natural Science Foundation of China(Grant No.42161024)the Central Financial Forestry and Grassland Science and Technology Extension Demonstration Project(2025)(Grant No.Xin[2025]TG 09)。
文摘Accurate quantification of carbon and water fluxes dynamics in arid and semi-arid ecosystems is a critical scientific challenge for regional carbon neutrality assessments and sustainable water resource management.In this study,we developed a multi-flux global sensitivity discriminant index(D_(sen))by integrating the Biome-BGCMuSo model with eddy covariance flux observations.This index was combined with a Bayesian optimization algorithm to conduct parameter optimization.The results demonstrated that:(1)Sensitivity analysis identified 13 highly sensitive parameters affecting carbon and water fluxes.Among these,the canopy light extinction coefficient(k)and the fraction of leaf N in Rubisco(FLNR)exhibited significantly higher sensitivity to carbon fluxes(GPP,NEE,Reco;D_(sen)>10%)compared to water flux(ET).This highlights the strong dependence of carbon cycle simulations on vegetation physiological parameters.(2)The Bayesian optimization framework efficiently converged 30 parameter spaces within 50 iterations,markedly improving carbon fluxes simulation accuracy.The Kling-Gupta efficiency(KGE)values for Gross Primary Production(GPP),Net Ecosystem Exchange(NEE),and Total Respiration(Reco)increased by 44.94%,69.23%and 123%,respectively.The optimization prioritized highly sensitive parameters,underscoring the necessity of parameter sensitivity stratification.(3)The optimized model effectively reproduced carbon sink characteristics in mountain meadows during the growing season(cumulative NEE=-375 g C/m^(2)).It revealed synergistic carbon-water fluxes interactions governed by coupled photosynthesis-stomatal pathways and identified substrate supply limitations on heterotrophic respiration.This study proposes a novel multi-flux sensitivity index and an efficient optimization framework,elucidating the coupling mechanisms between vegetation physiological regulation(k,FLNR)and environmental stressors(VPD,SWD)in carbonwater cycles.The methodology offers a practical approach for arid ecosystem model optimization and provides theoretical insights for grassland management through canopy structure regulation and water-use efficiency enhancement.
文摘In engineering systems,uncertainties in input parameters can significantly influence the output responses.This paper proposes a model distance-based approach to perform global sensitivity analysis for quantifying the influence of input uncertainties on multiple responses in an engineering system.The sensitivity indices are determined by comparing a reference model that incorporates all system uncertainties,with an altered model,where specific uncertainties are constrained.The proposed framework employs probability distance measures such as Hellinger distance,Kullback-Leibler divergence,and I2 norm which are based on joint probability density functions.The study also demonstrates the equivalence between the l2 norm-based approach and Sobol's analysis in multivariate sensitivity context.The proposed methodology effectively manages correlated random variables,accommodates both Gaussian and non-Gaussian distributions,and allows for the grouping of input variables.Ilustrative examples consist of static analysis of a truss system and dynamic analysis of a frame subjected to seismic excitation.The sensitivity indices are estimated using brute-force Monte Carlo simulations.The relative ranking of these sensitivity indices can be utilized to identify the most and least significant variables contributing to the response uncertainty.The numerical results show a consistent ranking of input variables across different probability measures,indicating the robustness of proposed framework.
基金support from the National Natural Science Foundation of China(Grant Nos.52174123&52274222).
文摘This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior.Physical models involving deformation,such as collisions,vibrations,and penetration,are devel-oped using the material point method.To reduce the computational cost of Monte Carlo simulations,response surface models are created as surrogate models for the material point system to approximate its dynamic behavior.An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order,effectively balancing the accuracy and computational efficiency of the surrogate model.Based on the sparse polynomial chaos expansion,sensitivity analysis is conducted using the global finite difference and Sobol methods.Several examples of structural dynamics are provided to demonstrate the effectiveness of the proposed method in addressing structural dynamics problems.
基金Dalian Municipal Natural Science Foundation under Grant No.2019RD01。
文摘Economic losses and catastrophic casualties may occur once super high-rise structures are struck by low-probability but high-consequence scenarios of concurrent earthquakes and winds. Therefore, accurately predicting multi-hazard dynamic responses to super high-rise structures has significant engineering and scientific value. This study performed a parametric global sensitivity analysis (GSA) for multi-hazard dynamic response prediction of super high-rise structures using the multiple-degree-of-freedom shear (MFS) model. Polynomial chaos Kriging (PCK) was introduced to build a surrogate model that allowed GSA to be combined with Sobol’ indices. Monte Carlo simulation (MCS) is also conducted for the comparison to verify the accuracy and efficiency of the PCK method. Parametric sensitivity analysis is performed for a wide range of aleatory uncertainty (intensities of coupled multi-hazard), epistemic uncertainty (bending stiffness, k_(m);shear stiffness, kq;density, ρ;and damping ratio, ξ), probability distribution types, and coefficients of variation. The results indicate that epistemic uncertainty parameters, k_(m), ρ, and ξ dramatically affect the multi-hazard dynamic responses of super high-rise structures;in addition, Sobol’ indices between the normal and lognormal distributions are insignificant, while the variation levels have remarkably influenced the sensitivity indices.
基金supported by the National Natural Science Foundation of China[grant numbers 42192553 and 41922036]the Fundamental Research Funds for the Central Universities–Cemac“GeoX”Interdisciplinary Program[grant number 020714380207]。
文摘While steady improvements have been achieved for the track forecasts of typhoons,there has been a lack of improvement for intensity forecasts.One challenge for intensity forecasts is to capture the rapid intensification(RI),whose nonlinear characteristics impose great difficulties for numerical models.The ensemble sensitivity analysis(ESA)method is used here to analyze the initial conditions that contribute to typhoon intensity forecasts,especially with RI.Six RI processes from five typhoons(Chaba,Haima,Meranti,Sarika,and Songda)in 2016,are applied with ESA,which also gives a composite initial condition that favors subsequent RI.Results from individual cases have generally similar patterns of ESA,but with different magnitudes,when various cumulus parameterization schemes are applied.To draw the initial conditions with statistical significance,sample-mean azimuthal components of ESA are obtained.Results of the composite sensitivity show that typhoons that experience RI in 24 h favor enhanced primary circulation from low to high levels,intensified secondary circulation with increased radial inflow at lower levels and increased radial outflow at upper levels,a prominent warm core at around 300 hPa,and increased humidity at low levels.As the forecast lead time increases,the patterns of ESA are retained,while the sensitivity magnitudes decay.Given the general and quantitative composite sensitivity along with associated uncertainties for different cumulus parameterization schemes,appropriate sampling of the composite sensitivity in numerical models could be beneficial to capturing the RI and improving the forecasting of typhoon intensity.
基金supported by the National Key Research and Development Program of China(No.2022YFC3701205)the National Natural Science Foundation of China(No.41975173)the Science and Technology Development Fund of the Chinese Academy of Meteorological Sciences(No.2021KJ011)。
文摘In recent years,incidents of simultaneous exceedance of PM_(2.5)and O_(3) concentrations,termed PM_(2.5)and O_(3) co-pollution events,have frequently occurred in China.This study conducted atmospheric circulation analysis on two typical co-pollution events in Beijing,occurring from July 22 to July 28,2019,and from April 25 to May 2,2020.These events were categorized into pre-trough southerly airflow type(Type 1)and post-trough northwest flow type(Type 2).Subsequently,sensitivity analyses using the GRAPES-CUACE adjoint model were performed to quantify the contributions of precursor emissions from Beijing and surrounding areas to PM_(2.5)and O_(3) concentrations in Beijing for two types of co-pollution.The results indicated that the spatiotemporal distribution of sensitive source region varied among different circulation types.Primary PM_(2.5)(PPM_(2.5))emissions from Hebei contributed the most to the 24-hour average PM_(2.5)(24-h PM_(2.5))peak concentration(41.6%-45.4%),followed by Beijing emissions(31%-35.7%).The maximum daily 8-hour average ozone peak concentration was primarily influenced by the emissions from Hebei and Beijing,with contribution ratios respectively of 32.8%-44.8% and 29%-42.1%.Additionally,NO_(x)emissions were the main contributors in Type 1,while both NO_(x)and VOCs emissions contributed similarly in Type 2.The iterative emission reduction experiments for two types of co-pollution indicated that Type 1 required emission reductions in NO_(x)(52.4%-71.8%)and VOCs(14.1%-33.8%)only.In contrast,Type 2 required combined emission reductions in NO_(x)(37.0%-65.1%),VOCs(30.7%-56.2%),and PPM_(2.5)(31%-46.9%).This study provided a reference for controlling co-pollution events and improving air quality in Beijing.
基金funded by the INTER program and cofunded by the Fond National de la Recherche,Luxembourg(FNR)and the Fund for Scientific Research-FNRS,Belgium(F.R.S-FNRS),T.0233.20-‘Sustainable Residential Densification’project(SusDens,2020–2024).
文摘The impact of different global and local variables in urban development processes requires a systematic study to fully comprehend the underlying complexities in them.The interplay between such variables is crucial for modelling urban growth to closely reflects reality.Despite extensive research,ambiguity remains about how variations in these input variables influence urban densification.In this study,we conduct a global sensitivity analysis(SA)using a multinomial logistic regression(MNL)model to assess the model’s explanatory and predictive power.We examine the influence of global variables,including spatial resolution,neighborhood size,and density classes,under different input combinations at a provincial scale to understand their impact on densification.Additionally,we perform a stepwise regression to identify the significant explanatory variables that are important for understanding densification in the Brussels Metropolitan Area(BMA).Our results indicate that a finer spatial resolution of 50 m and 100 m,smaller neighborhood size of 5×5 and 3×3,and specific density classes—namely 3(non-built-up,low and high built-up)and 4(non-built-up,low,medium and high built-up)—optimally explain and predict urban densification.In line with the same,the stepwise regression reveals that models with a coarser resolution of 300 m lack significant variables,reflecting a lower explanatory power for densification.This approach aids in identifying optimal and significant global variables with higher explanatory power for understanding and predicting urban densification.Furthermore,these findings are reproducible in a global urban context,offering valuable insights for planners,modelers and geographers in managing future urban growth and minimizing modelling.
文摘Kangbao County is located in the northwest of Bashang in Hebei Province,which is a sub-arid area in the middle temperate zone,with a cold and arid climate and frequent disastrous weather.The meteorological data of Kangbao County Meteorological Station from 1994 to 2023 were selected,and the meteorological elements such as air pressure,temperature,precipitation,wind,relative humidity,sunshine,thunderstorm,hail,gale,rainstorm,fog,and snow cover were counted.The climate background analysis and high-impact weather analysis were carried out in combination with the topographic characteristics,geographical location,and climate characteristics.The results of meteorological sensitivity survey in the park showed that industries such as food,agriculture and new energy are very sensitive to temperature.During the visit to the enterprises in the park,it was found that heavy precipitation,snow,strong winds and hail had a great impact on many industries,and it was recommended to carry out long-term planning and reasonable design of buildings.It should pay close attention to forecasts and early warnings,formulate emergency plans for high-impact weather defense,and actively take preventive measures.
基金The Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXLX13_110)the Young Scientists Fund of National Natural Science Foundation of China(No.51408253)the Young Scientists Fund of Huaiyin Institute of Technology(No.491713328)
文摘This paper puts forward a rigorous approach for a sensitivity analysis of stochastic user equilibrium with the elastic demand （SUEED） model. First, proof is given for the existence of derivatives of output variables with respect to the perturbation parameters for the SUEED model. Then by taking advantage of the gradient-based method for sensitivity analysis of a general nonlinear program, detailed formulae are developed for calculating the derivatives of designed variables with respect to perturbation parameters at the equilibrium state of the SUEED model. This method is not only applicable for a sensitivity analysis of the logit-type SUEED problem, but also for the probit-type SUEED problem. The application of the proposed method in a numerical example shows that the proposed method can be used to approximate the equilibrium link flow solutions for both logit-type SUEED and probit-type SUEED problems when small perturbations are introduced in the input parameters.
基金supported by Tianjin Research Program of Application Foundation and Advanced Technology of China (Grant No.11JCZDJC22700)National Natural Science Foundation of China (GrantNo. 51075295,Grant No. 50675151)+1 种基金National High-tech Research and Development Program of China (863 Program,Grant No.2007AA042001)PhD Programs Foundation of Ministry of Education of China (Grant No. 20060056018)
文摘Parallel kinematic machines （PKMs） have the advantages of a compact structure,high stiffness,a low moving inertia,and a high load/weight ratio.PKMs have been intensively studied since the 1980s,and are still attracting much attention.Compared with extensive researches focus on their type/dimensional synthesis,kinematic/dynamic analyses,the error modeling and separation issues in PKMs are not studied adequately,which is one of the most important obstacles in its commercial applications widely.Taking a 3-PRS parallel manipulator as an example,this paper presents a separation method of source errors for 3-DOF parallel manipulator into the compensable and non-compensable errors effectively.The kinematic analysis of 3-PRS parallel manipulator leads to its six-dimension Jacobian matrix,which can be mapped into the Jacobian matrix of actuations and constraints,and then the compensable and non-compensable errors can be separated accordingly.The compensable errors can be compensated by the kinematic calibration,while the non-compensable errors may be adjusted by the manufacturing and assembling process.Followed by the influence of the latter,i.e.,the non-compensable errors,on the pose error of the moving platform through the sensitivity analysis with the aid of the Monte-Carlo method,meanwhile,the configurations of the manipulator are sought as the pose errors of the moving platform approaching their maximum.The compensable and non-compensable errors in limited-DOF parallel manipulators can be separated effectively by means of the Jacobian matrix of actuations and constraints,providing designers with an informative guideline to taking proper measures for enhancing the pose accuracy via component tolerancing and/or kinematic calibration,which can lay the foundation for the error distinguishment and compensation.
基金Supported by National Natural Science Foundation of China(Grant No.51305222)National Key Scientific and Technological Program of China(Grant No.2013ZX04001-021)
文摘Parallel robots with SCARA（selective compliance assembly robot arm） motions are utilized widely in the field of high speed pick-and-place manipulation. Error modeling for these robots generally simplifies the parallelogram structures included by the robots as a link. As the established error model fails to reflect the error feature of the parallelogram structures, the effect of accuracy design and kinematic calibration based on the error model come to be undermined. An error modeling methodology is proposed to establish an error model of parallel robots with parallelogram structures. The error model can embody the geometric errors of all joints, including the joints of parallelogram structures. Thus it can contain more exhaustively the factors that reduce the accuracy of the robot. Based on the error model and some sensitivity indices defined in the sense of statistics, sensitivity analysis is carried out. Accordingly, some atlases are depicted to express each geometric error’s influence on the moving platform’s pose errors. From these atlases, the geometric errors that have greater impact on the accuracy of the moving platform are identified, and some sensitive areas where the pose errors of the moving platform are extremely sensitive to the geometric errors are also figured out. By taking into account the error factors which are generally neglected in all existing modeling methods, the proposed modeling method can thoroughly disclose the process of error transmission and enhance the efficacy of accuracy design and calibration.
基金Supported by National Key Basic Research Program of China(973 Program,Grant No.2014CB046405)Hebei Provincial Applied Basic Research Program(Grant No.12962147D)National Natural Science Foundation of China(Grant No.51375423)
文摘The previous sensitivity analysis researches are not accurate enough and also have the limited reference value, because those mathematical models are relatively simple and the change of the load and the initial displacement changes of the piston are ignored, even experiment verification is not conducted. Therefore, in view of deficiencies above, a nonlinear mathematical model is established in this paper, including dynamic characteristics of servo valve, nonlinear characteristics of pressure-flow, initial displacement of servo cylinder piston and friction nonlinearity. The transfer function block diagram is built for the hydraulic drive unit closed loop position control, as well as the state equations. Through deriving the time-varying coefficient items matrix and time-varying free items matrix of sensitivity equations respectively, the expression of sensitivity equations based on the nonlinear mathematical model are obtained. According to structure parameters of hydraulic drive unit, working parameters, fluid transmission characteristics and measured friction-velocity curves, the simulation analysis of hydraulic drive unit is completed on the MATLAB/Simulink simulation platform with the displacement step 2 mm, 5 mm and 10 mm, respectively. The simulation results indicate that the developed nonlinear mathematical model is sufficient by comparing the characteristic curves of experimental step response and simulation step response under different constant load. Then, the sensitivity function time-history curves of seventeen parameters are obtained, basing on each state vector time-history curve of step response characteristic. The maximum value of displacement variation percentage and the sum of displacement variation absolute values in the sampling time are both taken as sensitivity indexes. The sensitivity indexes values above are calculated and shown visually in histograms under different working conditions, and change rules are analyzed. Then the sensitivity indexes values of four measurable parameters, such as supply pressure, proportional gain, initial position of servo cylinder piston and load force, are verified experimentally on test platform of hydraulic drive unit, and the experimental research shows that the sensitivity analysis results obtained through simulation are approximate to the test results. This research indicates each parameter sensitivity characteristics of hydraulic drive unit, the performance-affected main parameters and secondary parameters are got under different working conditions, which will provide the theoretical foundation for the control compensation and structure optimization of hydraulic drive unit.
基金National Key Basic Research Program of China,No.2010CB428403National Grand Science and Technology Special Project of Water Pollution Control and Improvement,No.2009ZX07210-006
文摘Sensitivity analysis of hydrological model is the key for model uncertainty quantification. However, how to effectively validate model and identify the dominant parameters for distributed hydrological models is a bottle-neck to achieve parameters optimization. For this reason, a new approach was proposed in this paper, in which the support vector machine was used to construct the response surface at first. Then it integrates the SVM-based response surface with the Sobol＇ method, i.e. the RSMSoboI＇ method, to quantify the parameter sensi- tivities. In this work, the distributed time-variant gain model （DTVGM） was applied to the Huaihe River Basin, which was used as a case to verify its validity and feasibility. We selected three objective functions （i.e. water balance coefficient WB, Nash-Sutcliffe efficiency coefficient NS, and correlation coefficient RC） to assess the model performance as the output responses for sensitivity analysis. The results show that the parameters gl and g2 are most important for all the objective functions, and they are almost the same to that of the classical approach. Furthermore, the RSMSobol method can not only achieve the quantification of the sensitivity, and also reduce the computational cost, with good accuracy compared to the classical approach. And this approach will be effective and reliable in the global sensitivity analysis for a complex modelling system.
基金Projects(51674188,51874229,51504182)supported by the National Natural Science Foundation of ChinaProject(2018KJXX-083)supported by Shaanxi Innovative Talents Cultivate Program-New-star Plan of Science and Technology,China
文摘The mechanical properties of cemented paste backfill(CPB) depend heavily on its pore structural characteristics and micro-structural changes. In order to explore the variation mechanisms of macro-mechanical characteristics and micro-structure of CPB. CPB specimens with different mass concentrations prepared from the full tailings of Xianglushan Tungsten Ore were micro-tests. Moreover, acquired pore digital images were processed by using the pores(particles) and cracks analysis system(PCAS), and a sensitivity analysis was performed. The results show that as the mass concentration of CPB increases from 70% to 78%, the porosity, the average pore area and the number of pores drop overall, leading to a decline in the pores opening degree and enhancing the mechanical characteristics. As the mass concentration of CPB increases, the trend of fractal dimension, probability entropy and roundness is reduced, constant and increased, which can result in an enhancement of the uniformity, an unchanged directionality and more round pores. According to the definition of sensitivity, the sensitivities of various micro-parameters were calculated and can be ranked as porosity > average pore area > number of pores > roundness > fractal dimension > probability entropy.
基金supported by the National Natural Science Foundation of China (No. 51175502)
文摘In the helicopter transmission systems, it is important to monitor and track the tooth damage evolution using lots of sensors and detection methods. This paper develops a novel approach for sensor selection based on physical model and sensitivity analysis. Firstly, a physical model of tooth damage and mesh stiffness is built. Secondly, some effective condition indicators （Cls） are presented, and the optimal Cls set is selected by comparing their test statistics according to Mann-Kendall test. Afterwards, the selected CIs are used to generate a health indicator （HI） through sen slop estimator. Then, the sensors are selected according to the monotonic relevance and sensitivity to the damage levels. Finally, the proposed method is verified by the simulation and experimental data. The results show that the approach can provide a guide for health monitor- ing of helicopter transmission systems, and it is effective to reduce the test cost and improve the system＇s reliability.
基金Innovation Plan of Aero Engine Complex System Safety by the Ministry of Education Chang Jiang Scholars of China (IRT0905)
文摘This paper presents an application of global sensitivity analysis for system safety analysis of reciprocating aircraft engine. Compared with local sensitivity analysis results, global sensitivity analysis could provide more information on parameter inter- actions, which are significant in complex system safety analysis. First, a deterministic aviation reciprocating engine thermody- namics model is developed and parameters of interest are defined as random variables. Then, samples are generated by Monte Carlo method for the parameters used in engine model on the basis of definition of factor distribution. Eventually, results from engine model are generated and importance indices are calculated. Based on the analysis results, design is improved to satisfy the airworthiness requirements. The results reveal that by using global sensitivity analysis, the parameters could be ranked with respect to their importance, including first order indices and total sensitivity indices. By reducing the uncertainty of parameters and adjusting the range of inputs, safety criteria would be satisfied.
基金supported by the National Natural Science Foundation of China(No.12002284)。
文摘Natural laminar flow technology can significantly reduce aircraft aerodynamic drag and has excellent technical appeal for transport aircraft development with high aerodynamic efficiency.Accurately and efficiently predicting the laminar-to-turbulent transition and revealing the maintenance mechanism of laminar flow in a transport aircraft’s flight environment are significant for developing natural laminar flow wings.In this research,we carry out natural laminar flow flight experiments with different Reynolds numbers and angles of attack.The critical N-factor is calibrated as 9.0 using flight experimental data and linear stability theory from a statistical perspective,which makes sure that the relative error of transition location is within 5%.We then implement a simplified e^(N) transition prediction method with a similar accuracy compared with linear stability theory.We compute the sensitivity information for the simplified eN method with an adjointbased method,using the automatic differentiation technique(ADjoint).The impact of Reynolds numbers and pressure distributions on TS waves is analyzed using the sensitivity information.Through the sensitivity analysis,we find that:favorable pressure gradients not only suppress the development of TS waves but also decrease their sensitivity to Reynolds numbers;there exist three special regions which are very sensitive to the pressure distribution,and the sensitivity decreases as the local favorable pressure gradient increases.The proposed sensitivity analysis method enables robust natural laminar flow wings design.
