The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce...The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable uncertainty.Therefore,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and improvement.This study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation strategies.Through an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant accidents.Seventeen uncertainty parameters of the ISAA program were meticulously screened.Using Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch calculations.Statistical analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure vessel.Uncertainty calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,respectively.The ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.展开更多
Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(i.e.type of distribution type and its parameters)of input rock properties emanating du...Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(i.e.type of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model response.This paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input data.The methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input properties.The estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic models.The proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of India.The proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of properties.Imprecise Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection efforts.Analyses performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample sizes.The accurate importance ranking of properties was only possible via samples of large sizes.Further,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.展开更多
Case history investigations have shown that pile foundations are more critically damaged in liquefiable soils than non-liquefiable soils.This study examines the differences in seismic response of pile foundations in l...Case history investigations have shown that pile foundations are more critically damaged in liquefiable soils than non-liquefiable soils.This study examines the differences in seismic response of pile foundations in liquefiable and non-liquefiable soils and their sensitivity to numerical model parameters.A two-dimensional finite element(FE)model is developed to simulate the experiment of a single pile foundation centrifuge in liquefiable soil subjected to earthquake motions and is validated against real-world test results.The differences in soil-pile seismic response of liquefiable and non-liquefiable soils are explored.Specifically,the first-order second-moment method(FOSM)is used for sensitivity analysis of the seismic response.The results show significant differences in seismic response for a soil-pile system between liquefiable and non-liquefiable soil.The seismic responses are found to be significantly larger in liquefiable soil than in non-liquefiable soil.Moreover,the pile bending moment was mainly affected by the kinematic effect in liquefiable soil,while the inertial effect was more significant in non-liquefiable soil.The controlling parameters of seismic response were PGA,soil density,and friction angle in liquefiable soil,while the pile bending moment was mainly controlled by PGA,the friction angle of soil,and shear modulus of loose sand in non-liquefiable soil.展开更多
Liquefaction is one of the most destructive phenomena caused by earthquakes,which has been studied in the issues of potential,triggering and hazard analysis.The strain energy approach is a common method to investigate...Liquefaction is one of the most destructive phenomena caused by earthquakes,which has been studied in the issues of potential,triggering and hazard analysis.The strain energy approach is a common method to investigate liquefaction potential.In this study,two Artificial Neural Network(ANN)models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept(W)by using laboratory test data.A large database was collected from the literature.One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model.To investigate the complex influence of fine content(FC)on liquefaction resistance,according to previous studies,the second database was arranged by samples with FC of less than 28%and was used to train the second ANN model.Then,two presented ANN models in this study,in addition to four extra available models,were applied to an additional 20 new samples for comparing their results to show the capability and accuracy of the presented models herein.Furthermore,a parametric sensitivity analysis was performed through Monte Carlo Simulation(MCS)to evaluate the effects of parameters and their uncertainties on the liquefaction resistance of soils.According to the results,the developed models provide a higher accuracy prediction performance than the previously publishedmodels.The sensitivity analysis illustrated that the uncertainties of grading parameters significantly affect the liquefaction resistance of soils.展开更多
For laser cladding a large temperature gradient easily weakened the surface quality by generating cracks and irregular coating surfaces,which in turn affected the bearing capacity and corrosion resistance of coatings ...For laser cladding a large temperature gradient easily weakened the surface quality by generating cracks and irregular coating surfaces,which in turn affected the bearing capacity and corrosion resistance of coatings in the rapid heating and cooling process.The response surface methodology(RSM)was used to predict coating cracks by changing the powder ratio,energy density,and preheating temperature,which obtained the relevant mathematical model.After that,the sensitivity of the crack length to process parameters was analyzed based on the sensitivity analysis method.The effect of Ni60/WC composite powder process parameters on the surface quality was revealed in laser cladding.The crack length first decreased and then increased,and the Smooth decreased with the increased powder ratio.The crack length and Smooth increased with the increased energy density.The crack length decreased and Smooth increased with the increased preheating temperature.Sensitivity analysis showed that the crack length and Smooth were the most sensitive to the powder ratio.Therefore,the process parameters were reasonably selected to control the surface quality.The mathematical model and sensitivity analysis method in the work could improve the surface quality,which provided a theoretical basis for the prediction and control of laser cladding cracks.展开更多
Estimating the oil-water temperatures in flowlines is challenging especially in deepwater and ultra-deepwater offshore applications where issues of flow assurance and dramatic heat transfer are likely to occur due to ...Estimating the oil-water temperatures in flowlines is challenging especially in deepwater and ultra-deepwater offshore applications where issues of flow assurance and dramatic heat transfer are likely to occur due to the temperature difference between the fluids and the surroundings. Heat transfer analysis is very important for the prediction and prevention of deposits in oil and water flowlines, which could impede the flow and give rise to huge financial losses. Therefore, a 3D mathematical model of oil-water Newtonian flow under non-isothermal conditions is established to explore the complex mechanisms of the two-phase oil-water transportation and heat transfer in different flowline inclinations. In this work, a non-isothermal two-phase flow model is first modified and then implemented in the InterFoam solver by introducing the energy equation using OpenFOAM® code. The Low Reynolds Number (LRN) k-ε turbulence model is utilized to resolve the turbulence phenomena within the oil and water mixtures. The flow patterns and the local heat transfer coefficients (HTC) for two-phase oil-water flow at different flowlines inclinations (0°, +4°, +7°) are validated by the experimental literature results and the relative errors are also compared. Global sensitivity analysis is then conducted to determine the effect of the different parameters on the performance of the produced two-phase hydrocarbon systems for effective subsea fluid transportation. Thereafter, HTC and flow patterns for oil-water flows at downward inclinations of 4°, and 7° can be predicted by the models. The velocity distribution, pressure gradient, liquid holdup, and temperature variation at the flowline cross-sections are simulated and analyzed in detail. Consequently, the numerical model can be generally applied to compute the global properties of the fluid and other operating parameters that are beneficial in the management of two-phase oil-water transportation.展开更多
Natural gas hydrate(NGH)is an important future resource for the 21st century and a strategic resource with potential for commercial development in the third energy transition.It is of great significance to accurately ...Natural gas hydrate(NGH)is an important future resource for the 21st century and a strategic resource with potential for commercial development in the third energy transition.It is of great significance to accurately predict the productivity of hydrate-bearing sediments(HBS).The multi-phase seepage parameters of HBS include permeability,porosity,which is closely related to permeability,and hydrate saturation,which has a direct impact on hydrate content.Existing research has shown that these multi-phase seepage parameters have a great impact on HBS productivity.Permeability directly affects the transmission of pressure-drop and discharge of methane gas,porosity and initial hydrate saturation affect the amount of hydrate decomposition and transmission process of pressure-drop,and also indirectly affect temperature variation of the reservoir.Considering the spatial heterogeneity of multi-phase seepage parameters,a depressurization production model with layered heterogeneity is established based on the clayey silt hydrate reservoir at W11 station in the Shenhu Sea area of the South China Sea.Tough+Hydrate software was used to calculate the production model;the process of gas production and seepage parameter evolution under different multi-phase seepage conditions were obtained.A sensitivity analysis of the parameters affecting the reservoir productivity was conducted so that:(a)a HBS model with layered heterogeneity can better describe the transmission process of pressure and thermal compensation mechanism of hydrate reservoir;(b)considering the multi-phase seepage parameter heterogeneity,the influence degrees of the parameters on HBS productivity were permeability,porosity and initial hydrate saturation,in order from large to small,and the influence of permeability was significantly greater than that of other parameters;(c)the production potential of the clayey silt reservoir should not only be determined by hydrate content or seepage capacity,but also by the comprehensive effect of the two;and(d)time scales need to be considered when studying the effects of changes in multi-phase seepage parameters on HBS productivity.展开更多
Simulations and predictions using numerical models show considerable uncertainties,and parameter uncertainty is one of the most important sources.It is impractical to improve the simulation and prediction abilities by...Simulations and predictions using numerical models show considerable uncertainties,and parameter uncertainty is one of the most important sources.It is impractical to improve the simulation and prediction abilities by reducing the uncertainties of all parameters.Therefore,identifying the sensitive parameters or parameter combinations is crucial.This study proposes a novel approach:conditional nonlinear optimal perturbations sensitivity analysis(CNOPSA)method.The CNOPSA method fully considers the nonlinear synergistic effects of parameters in the whole parameter space and quantitatively estimates the maximum effects of parameter uncertainties,prone to extreme events.Results of the analytical g-function test indicate that the CNOPSA method can effectively identify the sensitivity of variables.Numerical results of the theoretical five-variable grassland ecosystem model show that the maximum influence of the simulated wilted biomass caused by parameter uncertainty can be estimated and computed by employing the CNOPSA method.The identified sensitive parameters can easily change the simulation or prediction of the wilted biomass,which affects the transformation of the grassland state in the grassland ecosystem.The variance-based approach may underestimate the parameter sensitivity because it only considers the influence of limited parameter samples from a statistical view.This study verifies that the CNOPSA method is effective and feasible for exploring the important and sensitive physical parameters or parameter combinations in numerical models.展开更多
The structural response of a single-layer reticulated dome to external explosions is shaped by many variables,and the associated uncertainties imply non-deterministic results.Existing deterministic methods for predict...The structural response of a single-layer reticulated dome to external explosions is shaped by many variables,and the associated uncertainties imply non-deterministic results.Existing deterministic methods for predicting the consequences of specific explosions do not account for these uncertainties.Therefore,the impact of the uncertainties associated with these input variables on the structures’response needs to be studied and quantified.In this study,a parametric uncertainty analysis was conducted first.Then,local and global sensitivity analyses were carried out to identify the drivers of the structural dynamic response.A probabilistic structural response model was established based on sensitive variables and a reasonable sample size.Furthermore,some deterministic empirical methods for explosion-resistance design,including the plane blast load model of CONWEP,the curved blast load model under the 50%assurance level,and the 20%mass-increased method,were used for evaluating their reliability.The results of the analyses revealed that the structural response of a single-layer reticulated dome to an external blast loading is lognormally distributed.Evidently,the MB0.5 method based on the curved reflector load model yielded results with a relatively stable assurance rate and reliability,but CONWEP did not;thus,the 1.2MB0.5 method can be used for making high-confidence simple predictions.In addition,the results indicated that the structural response is very sensitive to the explosion parameters.Based on these results,it is suggested that for explosion proofing,setting up a defensive barrier is more effective than structural strengthening.展开更多
The anti-sliding stability of a gravity dam along its foundation surface is a key problem in the design of gravity dams.In this study,a sensitivity analysis framework was proposed for investigating the factors affecti...The anti-sliding stability of a gravity dam along its foundation surface is a key problem in the design of gravity dams.In this study,a sensitivity analysis framework was proposed for investigating the factors affecting gravity dam anti-sliding stability along the foundation surface.According to the design specifications,the loads and factors affecting the stability of a gravity dam were comprehensively selected.Afterwards,the sensitivity of the factors was preliminarily analyzed using the Sobol method with Latin hypercube sampling.Then,the results of the sensitivity analysis were verified with those obtained using the Garson method.Finally,the effects of different sampling methods,probability distribution types of factor samples,and ranges of factor values on the analysis results were evaluated.A case study of a typical gravity dam in Yunnan Province of China showed that the dominant factors affecting the gravity dam anti-sliding stability were the anti-shear cohesion,upstream and downstream water levels,anti-shear friction coefficient,uplift pressure reduction coefficient,concrete density,and silt height.Choice of sampling methods showed no significant effect,but the probability distribution type and the range of factor values greatly affected the analysis results.Therefore,these two elements should be sufficiently considered to improve the reliability of the dam anti-sliding stability analysis.展开更多
Aiming at optimizing the energy consumption of HVAC,an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis(SA),named the sensitivity analysis combination method(SAC)...Aiming at optimizing the energy consumption of HVAC,an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis(SA),named the sensitivity analysis combination method(SAC).Based on the SA,neural network and the related settings about energy conservation of HVAC systems,such as cooling water temperature,chilled water temperature and supply air temperature,were optimized.Moreover,based on the data of the existing HVAC system,various optimal control methods ofHVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS.The results show that the proposed SA combination method can reduce significant computational load while maintaining an equivalent energy performance compared with traditional optimal control methods.展开更多
A challenge for the development of Land Surface Models(LSMs) is improving transpiration of water exchange and photosynthesis of carbon exchange between terrestrial plants and the atmosphere, both of which are governed...A challenge for the development of Land Surface Models(LSMs) is improving transpiration of water exchange and photosynthesis of carbon exchange between terrestrial plants and the atmosphere, both of which are governed by stoma in leaves. In the photosynthesis module of these LSMs, variations of parameters arising from diversity in plant functional types(PFTs) and climate remain unclear. Identifying sensitive parameters among all photosynthetic parameters before parameter estimation can not only reduce operation cost, but also improve the usability of photosynthesis models worldwide. Here, we analyzed 13 parameters of a biochemically-based photosynthesis model(FvCB), implemented in many LSMs, using two sensitivity analysis(SA) methods(i.e., the Sobol’ method and the Morris method) for setting up the parameter ensemble. Three different model performance metrics, i.e.,Root Mean Squared Error(RMSE), Nash Sutcliffe efficiency(NSE), and Standard Deviation(STDEV) were introduced for model assessment and sensitive parameters identification. The results showed that among all photosynthetic parameters only a small portion of parameters were sensitive, and the sensitive parameters were different across plant functional types: maximum rate of Rubisco activity(Vcmax25), maximum electron transport rate(Jmax25), triose phosphate use rate(TPU) and dark respiration in light(Rd) were sensitive in broad leafevergreen trees(BET), broad leaf-deciduous trees(BDT) and needle leaf-evergreen trees(NET), while only Vcmax25and TPU are sensitive in short vegetation(SV), dwarf trees and shrubs(DTS), and agriculture and grassland(AG). The two sensitivity analysis methods suggested a strong SA coherence;in contrast, different model performance metrics led to different SA results. This misfit suggests that more accurate values of sensitive parameters, specifically, species specific and seasonal variable parameters, are required to improve the performance of the FvCB model.展开更多
The prediction of processor performance has important referencesignificance for future processors. Both the accuracy and rationality of theprediction results are required. The hierarchical belief rule base (HBRB)can i...The prediction of processor performance has important referencesignificance for future processors. Both the accuracy and rationality of theprediction results are required. The hierarchical belief rule base (HBRB)can initially provide a solution to low prediction accuracy. However, theinterpretability of the model and the traceability of the results still warrantfurther investigation. Therefore, a processor performance prediction methodbased on interpretable hierarchical belief rule base (HBRB-I) and globalsensitivity analysis (GSA) is proposed. The method can yield more reliableprediction results. Evidence reasoning (ER) is firstly used to evaluate thehistorical data of the processor, followed by a performance prediction modelwith interpretability constraints that is constructed based on HBRB-I. Then,the whale optimization algorithm (WOA) is used to optimize the parameters.Furthermore, to test the interpretability of the performance predictionprocess, GSA is used to analyze the relationship between the input and thepredicted output indicators. Finally, based on the UCI database processordataset, the effectiveness and superiority of the method are verified. Accordingto our experiments, our prediction method generates more reliable andaccurate estimations than traditional models.展开更多
The absorber is the key unit in the post-combustion monoethanolamine(MEA)-based carbon dioxide(CO_(2))capture process.A rate-based dynamic model for the absorber is developed and validated using steady-state experimen...The absorber is the key unit in the post-combustion monoethanolamine(MEA)-based carbon dioxide(CO_(2))capture process.A rate-based dynamic model for the absorber is developed and validated using steady-state experimental data reported in open literature.Sensitivity analysis is performed with respect to important model parameters associated with the reaction,mass transport and phy-sical property relationships.Then,a singular value decomposition(SVD)-based subspace parameter estimation method is proposed to improve the model accu-racy.Finally,dynamic simulations are carried out to investigate the effects of the feed rate of lean MEA solution and the flue inlet conditions.Simulation results indicate that the established dynamic model can reasonably reflect the physical behavior of the absorber.Some new insights are gained from the simulation results.展开更多
To study active heat insulation roadway in high temperature mines,the typical high temperature roadway of−965 m in Zhujidong Coal Mine of Anhui,China,is selected as prototype.The ANSYS numerical simulation method is u...To study active heat insulation roadway in high temperature mines,the typical high temperature roadway of−965 m in Zhujidong Coal Mine of Anhui,China,is selected as prototype.The ANSYS numerical simulation method is used for sensitivity analysis of heat insulation layer with different thermal conductivity and thickness,as well as surrounding rock with different thermal conductivity and temperature on a heat-adjusting zone radius,surrounding rock temperature field and wall temperature.The results show that the heat-adjusting zone radius will entirely be in the right power index relationship to the ventilation time.Decrease in thermal conductivity and increase in thickness of insulation layer can effectively reduce the disturbance of airflow on the surrounding rock temperature,hence,beneficial for decreasing wall temperature.This favourable trend significantly decreases with ventilation time,increase in thermal conductivity and temperature of surrounding rock,heat-adjusting zone radius,surrounding rock temperature field,and wall temperature.Sensitivity analysis shows that the thermal physical properties of surrounding rock determine the temperature distribution of the roadway,hence,temperature of surrounding rock is considered as the most sensitive factor of all influencing factors.For the spray layer,thermal conductivity is more sensitive,compared to thickness.It is concluded that increase in the spray layer thickness is not as beneficial as using low thermal conductivity insulation material.Therefore,roadway preferential consideration should be given to the rocks with low temperature and thermal conductivity.The application of the insulation layer has positive significance for the thermal environment control in mine roadway,however,increase in the layer thickness without restriction has a limited effect on the thermal insulation.展开更多
To accelerate the achievement of China’s carbon neutrality goal and to study the factors affecting the geologic CO_(2)storage in the Ordos Basin,China’s National Key R&D Programs propose to select the Chang 6 oi...To accelerate the achievement of China’s carbon neutrality goal and to study the factors affecting the geologic CO_(2)storage in the Ordos Basin,China’s National Key R&D Programs propose to select the Chang 6 oil reservoir of the Yanchang Formation in the Ordos Basin as the target reservoir to conduct the geologic carbon capture and storage(CCS)of 100000 t per year.By applying the basic theories of disciplines such as seepage mechanics,multiphase fluid mechanics,and computational fluid mechanics and quantifying the amounts of CO_(2)captured in gas and dissolved forms,this study investigated the effects of seven factors that influence the CO_(2)storage capacity of reservoirs,namely reservoir porosity,horizontal permeability,temperature,formation stress,the ratio of vertical to horizontal permeability,capillary pressure,and residual gas saturation.The results show that the sensitivity of the factors affecting the gas capture capacity of CO_(2)decreases in the order of formation stress,temperature,residual gas saturation,horizontal permeability,and porosity.Meanwhile,the sensitivity of the factors affecting the dissolution capture capacity of CO_(2)decreases in the order of formation stress,residual gas saturation,temperature,horizontal permeability,and porosity.The sensitivity of the influencing factors can serve as the basis for carrying out a reasonable assessment of sites for future CO_(2)storage areas and for optimizing the design of existing CO_(2)storage areas.The sensitivity analysis of the influencing factors will provide basic data and technical support for implementing geologic CO_(2)storage and will assist in improving geologic CO_(2)storage technologies to achieve China’s carbon neutralization goal.展开更多
Background:Process-based models are widely used to simulate forest productivity,but complex parameterization and calibration challenge the application and development of these models.Sensitivity analysis of numerous p...Background:Process-based models are widely used to simulate forest productivity,but complex parameterization and calibration challenge the application and development of these models.Sensitivity analysis of numerous parameters is an essential step in model calibration and carbon flux simulation.However,parameters are not dependent on each other,and the results of sensitivity analysis usually vary due to different forest types and regions.Hence,global and representative sensitivity analysis would provide reliable information for simple calibration.Methods:To determine the contributions of input parameters to gross primary productivity(GPP)and net primary productivity(NPP),regression analysis and extended Fourier amplitude sensitivity testing(EFAST)were conducted for Biome-BGCMuSo to calculate the sensitivity index of the parameters at four observation sites under climate gradient from ChinaFLUX.Results:Generally,GPP and NPP were highly sensitive to C:Nleaf(C:N of leaves),Wint(canopy water interception coefficient),k(canopy light extinction coefficient),FLNR(fraction of leaf N in Rubisco),MRpern(coefficient of linear relationship between tissue N and maintenance respiration),VPDf(vapor pressure deficit complete conductance reduction),and SLA1(canopy average specific leaf area in phenological phase 1)at all observation sites.Various sensitive parameters occurred at four observation sites within different climate zones.GPP and NPP were particularly sensitive to FLNR,SLA1 and Wint,and C:Nleaf in temperate,alpine and subtropical zones,respectively.Conclusions:The results indicated that sensitivity parameters of China's forest ecosystems change with climate gradient.We found that parameter calibration should be performed according to plant functional type(PFT),and more attention needs to be paid to the differences in climate and environment.These findings contribute to determining the target parameters in field experiments and model calibration.展开更多
As a type of hydraulic rotary actuator,a helical hydraulic rotary actuator exhibits a large angle,high torque,and compact structure;hence,it has been widely used in various fields.However,its core technology is propri...As a type of hydraulic rotary actuator,a helical hydraulic rotary actuator exhibits a large angle,high torque,and compact structure;hence,it has been widely used in various fields.However,its core technology is proprietary to several companies and thus has not been disclosed.Furthermore,the relevant reports are primarily limited to the component level.The dynamic characteristics of the output when a helical rotary actuator is applied to a closed-loop system are investigated from the perspective of driving system design.Two main aspects are considered:one is to establish a reliable mathematical model and the other is to consider the effect of system parameter perturbation on the output.In this study,a detailed mechanical analysis of a helical rotary hydraulic cylinder is first performed,factors such as friction and load are considered,and an accurate dynamic model of the actuator is established.Subsequently,considering the nonlinear characteristics of pressure flow and the dynamic characteristics of the valve,a dynamic model of a valve-controlled helical rotary actuator angle closed-loop system is described based on sixth-order nonlinear state equations,which has never been reported previously.After deriving the system model,a sensitivity analysis of 23 main parameters in the model with a perturbation of 10%is performed under nine operating conditions.Finally,the system dynamics model and sensitivity analysis results are verified via a prototype experiment and co-simulation,which demonstrate the reliability of the theoretical results obtained in this study.The results provide an accurate mathematical model and analysis basis for the structural optimization or control compensation of similar systems.展开更多
In order to understand the effect of hardening ductility parameters and softening ductility parameters of the concrete damage plastic model in LS-DYNA,a sensitivity and reliability analysis of these parameters through...In order to understand the effect of hardening ductility parameters and softening ductility parameters of the concrete damage plastic model in LS-DYNA,a sensitivity and reliability analysis of these parameters through a convenient cube unit test was conducted. The results showed that the peak strength strain was independent of the hardening ductility parameter DH,but affected by AH,BH,and CH. The softening ductility was mainly related to the softening ductility parameter AS,but not affected by the damage ductility exponent BS. In case that the model with default parameters failed to match the AS-controlled damage softening phase,an optimized model with an AS correction was developed. The corrected model with the AS value of 2 matched well with the code model,and exhibited good feasibility in predicting the stress-strain curve of different grades of concrete. Moreover,the practicability of the corrected model was further validated by the conventional triaxial test. The simulated curve exhibited favorable consistence with the trial curve. Therefore,the model with parameter correction could provide a prospective reference for predicting the mechanical properties of concrete.展开更多
The groundwater constitutes the main source of drinking water for the populations in the Dabou region which is marked by a multiplication of socio-economic activities. The quality of groundwater is increasingly tested...The groundwater constitutes the main source of drinking water for the populations in the Dabou region which is marked by a multiplication of socio-economic activities. The quality of groundwater is increasingly tested by diverse sources of pollution caused by these human activities. In order to preserve their quality against any form of contamination, the present study aims to assess the groundwater vulnerability in this region and to highlight the relative importance of hydrogeological parameters which will be taken into account in this assessment. The assessment of the intrinsic vulnerability is to identify the most sensitive zones in order to prevent the groundwater pollution risks on the surface of the ground. To do it, the DRASTIC method is applied through a GIS. The GIS has also used to perform sensitivity analysis through the map removal and the single-parameter sensitivity analysis tests. The indexes calculated for the DRASTIC vulnerability map vary from 95 to 187 of the North towards the South. This vulnerability map presents four classes: very high (26.22%) in the South and the East, high (37.71%) in the Center, the North-East and the North-West, moderate (34.73%) to the North and the West and low (1.34%) in the North. The DRASTIC vulnerability map is heavily influenced by the impact of vadose zone and the depth to water table according to the first test. For the second test, it is the impact of vadose zone, the aquifer media and the soil media which have a more significant impact on the vulnerability map. Both sensitivity analysis tests confirm that the impact of vadose zone therefore sediment type is more implied in this assessment of the groundwater vulnerability in the Dabou region.展开更多
基金This work was supported financially by the National Natural Science Foundation of China(No.12375176).
文摘The phenomenology involved in severe accidents in nuclear reactors is highly complex.Currently,integrated analysis programs used for severe accident analysis heavily rely on custom empirical parameters,which introduce considerable uncertainty.Therefore,in recent years,the field of severe accidents has shifted its focus toward applying uncertainty analysis methods to quantify uncertainty in safety assessment programs,known as“best estimate plus uncertainty(BEPU).”This approach aids in enhancing our comprehension of these programs and their further development and improvement.This study concentrates on a third-generation pressurized water reactor equipped with advanced active and passive mitigation strategies.Through an Integrated Severe Accident Analysis Program(ISAA),numerical modeling and uncertainty analysis were conducted on severe accidents resulting from large break loss of coolant accidents.Seventeen uncertainty parameters of the ISAA program were meticulously screened.Using Wilks'formula,the developed uncertainty program code,SAUP,was employed to carry out Latin hypercube sampling,while ISAA was employed to execute batch calculations.Statistical analysis was then conducted on two figures of merit,namely hydrogen generation and the release of fission products within the pressure vessel.Uncertainty calculations revealed that hydrogen production and the fraction of fission product released exhibited a normal distribution,ranging from 182.784 to 330.664 kg and from 15.6 to 84.3%,respectively.The ratio of hydrogen production to reactor thermal power fell within the range of 0.0578–0.105.A sensitivity analysis was performed for uncertain input parameters,revealing significant correlations between the failure temperature of the cladding oxide layer,maximum melt flow rate,size of the particulate debris,and porosity of the debris with both hydrogen generation and the release of fission products.
文摘Traditional global sensitivity analysis(GSA)neglects the epistemic uncertainties associated with the probabilistic characteristics(i.e.type of distribution type and its parameters)of input rock properties emanating due to the small size of datasets while mapping the relative importance of properties to the model response.This paper proposes an augmented Bayesian multi-model inference(BMMI)coupled with GSA methodology(BMMI-GSA)to address this issue by estimating the imprecision in the momentindependent sensitivity indices of rock structures arising from the small size of input data.The methodology employs BMMI to quantify the epistemic uncertainties associated with model type and parameters of input properties.The estimated uncertainties are propagated in estimating imprecision in moment-independent Borgonovo’s indices by employing a reweighting approach on candidate probabilistic models.The proposed methodology is showcased for a rock slope prone to stress-controlled failure in the Himalayan region of India.The proposed methodology was superior to the conventional GSA(neglects all epistemic uncertainties)and Bayesian coupled GSA(B-GSA)(neglects model uncertainty)due to its capability to incorporate the uncertainties in both model type and parameters of properties.Imprecise Borgonovo’s indices estimated via proposed methodology provide the confidence intervals of the sensitivity indices instead of their fixed-point estimates,which makes the user more informed in the data collection efforts.Analyses performed with the varying sample sizes suggested that the uncertainties in sensitivity indices reduce significantly with the increasing sample sizes.The accurate importance ranking of properties was only possible via samples of large sizes.Further,the impact of the prior knowledge in terms of prior ranges and distributions was significant;hence,any related assumption should be made carefully.
基金National Science Foundation for Excellent Young Scholars of China under Grant No.51722801National Natural Science Foundation of China under Grant Nos.51808006 and 52078016。
文摘Case history investigations have shown that pile foundations are more critically damaged in liquefiable soils than non-liquefiable soils.This study examines the differences in seismic response of pile foundations in liquefiable and non-liquefiable soils and their sensitivity to numerical model parameters.A two-dimensional finite element(FE)model is developed to simulate the experiment of a single pile foundation centrifuge in liquefiable soil subjected to earthquake motions and is validated against real-world test results.The differences in soil-pile seismic response of liquefiable and non-liquefiable soils are explored.Specifically,the first-order second-moment method(FOSM)is used for sensitivity analysis of the seismic response.The results show significant differences in seismic response for a soil-pile system between liquefiable and non-liquefiable soil.The seismic responses are found to be significantly larger in liquefiable soil than in non-liquefiable soil.Moreover,the pile bending moment was mainly affected by the kinematic effect in liquefiable soil,while the inertial effect was more significant in non-liquefiable soil.The controlling parameters of seismic response were PGA,soil density,and friction angle in liquefiable soil,while the pile bending moment was mainly controlled by PGA,the friction angle of soil,and shear modulus of loose sand in non-liquefiable soil.
基金supported by the Scientific Innovation Group for Youths of Sichuan Province under Grant No.2019JDTD0017。
文摘Liquefaction is one of the most destructive phenomena caused by earthquakes,which has been studied in the issues of potential,triggering and hazard analysis.The strain energy approach is a common method to investigate liquefaction potential.In this study,two Artificial Neural Network(ANN)models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept(W)by using laboratory test data.A large database was collected from the literature.One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model.To investigate the complex influence of fine content(FC)on liquefaction resistance,according to previous studies,the second database was arranged by samples with FC of less than 28%and was used to train the second ANN model.Then,two presented ANN models in this study,in addition to four extra available models,were applied to an additional 20 new samples for comparing their results to show the capability and accuracy of the presented models herein.Furthermore,a parametric sensitivity analysis was performed through Monte Carlo Simulation(MCS)to evaluate the effects of parameters and their uncertainties on the liquefaction resistance of soils.According to the results,the developed models provide a higher accuracy prediction performance than the previously publishedmodels.The sensitivity analysis illustrated that the uncertainties of grading parameters significantly affect the liquefaction resistance of soils.
基金supported by Science and Technology Major Project of Fujian Province(Grant No.2020HZ03018).
文摘For laser cladding a large temperature gradient easily weakened the surface quality by generating cracks and irregular coating surfaces,which in turn affected the bearing capacity and corrosion resistance of coatings in the rapid heating and cooling process.The response surface methodology(RSM)was used to predict coating cracks by changing the powder ratio,energy density,and preheating temperature,which obtained the relevant mathematical model.After that,the sensitivity of the crack length to process parameters was analyzed based on the sensitivity analysis method.The effect of Ni60/WC composite powder process parameters on the surface quality was revealed in laser cladding.The crack length first decreased and then increased,and the Smooth decreased with the increased powder ratio.The crack length and Smooth increased with the increased energy density.The crack length decreased and Smooth increased with the increased preheating temperature.Sensitivity analysis showed that the crack length and Smooth were the most sensitive to the powder ratio.Therefore,the process parameters were reasonably selected to control the surface quality.The mathematical model and sensitivity analysis method in the work could improve the surface quality,which provided a theoretical basis for the prediction and control of laser cladding cracks.
文摘Estimating the oil-water temperatures in flowlines is challenging especially in deepwater and ultra-deepwater offshore applications where issues of flow assurance and dramatic heat transfer are likely to occur due to the temperature difference between the fluids and the surroundings. Heat transfer analysis is very important for the prediction and prevention of deposits in oil and water flowlines, which could impede the flow and give rise to huge financial losses. Therefore, a 3D mathematical model of oil-water Newtonian flow under non-isothermal conditions is established to explore the complex mechanisms of the two-phase oil-water transportation and heat transfer in different flowline inclinations. In this work, a non-isothermal two-phase flow model is first modified and then implemented in the InterFoam solver by introducing the energy equation using OpenFOAM® code. The Low Reynolds Number (LRN) k-ε turbulence model is utilized to resolve the turbulence phenomena within the oil and water mixtures. The flow patterns and the local heat transfer coefficients (HTC) for two-phase oil-water flow at different flowlines inclinations (0°, +4°, +7°) are validated by the experimental literature results and the relative errors are also compared. Global sensitivity analysis is then conducted to determine the effect of the different parameters on the performance of the produced two-phase hydrocarbon systems for effective subsea fluid transportation. Thereafter, HTC and flow patterns for oil-water flows at downward inclinations of 4°, and 7° can be predicted by the models. The velocity distribution, pressure gradient, liquid holdup, and temperature variation at the flowline cross-sections are simulated and analyzed in detail. Consequently, the numerical model can be generally applied to compute the global properties of the fluid and other operating parameters that are beneficial in the management of two-phase oil-water transportation.
基金supported by the National Natural Science Foundation of China(Grant Nos.42276224,and 42206230)the Jilin Scientific and Technological Development Program(Grant No.20190303083SF)+2 种基金the International Cooperation Key Laboratory of Underground Energy Development and Geological Restoration(Grant No.YDZJ202102CXJD014)the Interdisciplinary Integration and Innovation Project of JLU(Grant No.JLUXKJC2021ZZ18)the Graduate Innovation Fund of Jilin University(Grant No.2023CX100)。
文摘Natural gas hydrate(NGH)is an important future resource for the 21st century and a strategic resource with potential for commercial development in the third energy transition.It is of great significance to accurately predict the productivity of hydrate-bearing sediments(HBS).The multi-phase seepage parameters of HBS include permeability,porosity,which is closely related to permeability,and hydrate saturation,which has a direct impact on hydrate content.Existing research has shown that these multi-phase seepage parameters have a great impact on HBS productivity.Permeability directly affects the transmission of pressure-drop and discharge of methane gas,porosity and initial hydrate saturation affect the amount of hydrate decomposition and transmission process of pressure-drop,and also indirectly affect temperature variation of the reservoir.Considering the spatial heterogeneity of multi-phase seepage parameters,a depressurization production model with layered heterogeneity is established based on the clayey silt hydrate reservoir at W11 station in the Shenhu Sea area of the South China Sea.Tough+Hydrate software was used to calculate the production model;the process of gas production and seepage parameter evolution under different multi-phase seepage conditions were obtained.A sensitivity analysis of the parameters affecting the reservoir productivity was conducted so that:(a)a HBS model with layered heterogeneity can better describe the transmission process of pressure and thermal compensation mechanism of hydrate reservoir;(b)considering the multi-phase seepage parameter heterogeneity,the influence degrees of the parameters on HBS productivity were permeability,porosity and initial hydrate saturation,in order from large to small,and the influence of permeability was significantly greater than that of other parameters;(c)the production potential of the clayey silt reservoir should not only be determined by hydrate content or seepage capacity,but also by the comprehensive effect of the two;and(d)time scales need to be considered when studying the effects of changes in multi-phase seepage parameters on HBS productivity.
基金supported by the National Nature Science Foundation of China(41975132)the Guangdong Major Project of Basic and Applied Basic Research(Grant No.2020B0301030004).
文摘Simulations and predictions using numerical models show considerable uncertainties,and parameter uncertainty is one of the most important sources.It is impractical to improve the simulation and prediction abilities by reducing the uncertainties of all parameters.Therefore,identifying the sensitive parameters or parameter combinations is crucial.This study proposes a novel approach:conditional nonlinear optimal perturbations sensitivity analysis(CNOPSA)method.The CNOPSA method fully considers the nonlinear synergistic effects of parameters in the whole parameter space and quantitatively estimates the maximum effects of parameter uncertainties,prone to extreme events.Results of the analytical g-function test indicate that the CNOPSA method can effectively identify the sensitivity of variables.Numerical results of the theoretical five-variable grassland ecosystem model show that the maximum influence of the simulated wilted biomass caused by parameter uncertainty can be estimated and computed by employing the CNOPSA method.The identified sensitive parameters can easily change the simulation or prediction of the wilted biomass,which affects the transformation of the grassland state in the grassland ecosystem.The variance-based approach may underestimate the parameter sensitivity because it only considers the influence of limited parameter samples from a statistical view.This study verifies that the CNOPSA method is effective and feasible for exploring the important and sensitive physical parameters or parameter combinations in numerical models.
基金the financial support from the China Postdoctora Science Foundation (project No. 2021M690406)the financial supports from the National Natural Science Foundation of China (project Nos. 51708521, 51778183)
文摘The structural response of a single-layer reticulated dome to external explosions is shaped by many variables,and the associated uncertainties imply non-deterministic results.Existing deterministic methods for predicting the consequences of specific explosions do not account for these uncertainties.Therefore,the impact of the uncertainties associated with these input variables on the structures’response needs to be studied and quantified.In this study,a parametric uncertainty analysis was conducted first.Then,local and global sensitivity analyses were carried out to identify the drivers of the structural dynamic response.A probabilistic structural response model was established based on sensitive variables and a reasonable sample size.Furthermore,some deterministic empirical methods for explosion-resistance design,including the plane blast load model of CONWEP,the curved blast load model under the 50%assurance level,and the 20%mass-increased method,were used for evaluating their reliability.The results of the analyses revealed that the structural response of a single-layer reticulated dome to an external blast loading is lognormally distributed.Evidently,the MB0.5 method based on the curved reflector load model yielded results with a relatively stable assurance rate and reliability,but CONWEP did not;thus,the 1.2MB0.5 method can be used for making high-confidence simple predictions.In addition,the results indicated that the structural response is very sensitive to the explosion parameters.Based on these results,it is suggested that for explosion proofing,setting up a defensive barrier is more effective than structural strengthening.
基金supported by the National Natural Science Foundation of China(Grant No.52079120).
文摘The anti-sliding stability of a gravity dam along its foundation surface is a key problem in the design of gravity dams.In this study,a sensitivity analysis framework was proposed for investigating the factors affecting gravity dam anti-sliding stability along the foundation surface.According to the design specifications,the loads and factors affecting the stability of a gravity dam were comprehensively selected.Afterwards,the sensitivity of the factors was preliminarily analyzed using the Sobol method with Latin hypercube sampling.Then,the results of the sensitivity analysis were verified with those obtained using the Garson method.Finally,the effects of different sampling methods,probability distribution types of factor samples,and ranges of factor values on the analysis results were evaluated.A case study of a typical gravity dam in Yunnan Province of China showed that the dominant factors affecting the gravity dam anti-sliding stability were the anti-shear cohesion,upstream and downstream water levels,anti-shear friction coefficient,uplift pressure reduction coefficient,concrete density,and silt height.Choice of sampling methods showed no significant effect,but the probability distribution type and the range of factor values greatly affected the analysis results.Therefore,these two elements should be sufficiently considered to improve the reliability of the dam anti-sliding stability analysis.
基金supported by National Key R&D Program of China(No.2020YFC2006602)National Natural Science Foundation of China(Nos.62072324,61876217,61876121,61772357)+1 种基金University Natural Science Foundation of Jiangsu Province(No.21KJA520005)Primary Research and Development Plan of Jiangsu Province(No.BE2020026).
文摘Aiming at optimizing the energy consumption of HVAC,an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis(SA),named the sensitivity analysis combination method(SAC).Based on the SA,neural network and the related settings about energy conservation of HVAC systems,such as cooling water temperature,chilled water temperature and supply air temperature,were optimized.Moreover,based on the data of the existing HVAC system,various optimal control methods ofHVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS.The results show that the proposed SA combination method can reduce significant computational load while maintaining an equivalent energy performance compared with traditional optimal control methods.
基金supported by the CAS"Light of West China"Program (No.[2020]82)Key technology projects of Inner Mongolia Autonomous Region (Grant No.2020GG0306)+1 种基金Science and Technology Plan Projects of Alxa League (Grant No.AMY2020-18)Natural Science Foundation of Gansu Province (No.21JR7RA038).
文摘A challenge for the development of Land Surface Models(LSMs) is improving transpiration of water exchange and photosynthesis of carbon exchange between terrestrial plants and the atmosphere, both of which are governed by stoma in leaves. In the photosynthesis module of these LSMs, variations of parameters arising from diversity in plant functional types(PFTs) and climate remain unclear. Identifying sensitive parameters among all photosynthetic parameters before parameter estimation can not only reduce operation cost, but also improve the usability of photosynthesis models worldwide. Here, we analyzed 13 parameters of a biochemically-based photosynthesis model(FvCB), implemented in many LSMs, using two sensitivity analysis(SA) methods(i.e., the Sobol’ method and the Morris method) for setting up the parameter ensemble. Three different model performance metrics, i.e.,Root Mean Squared Error(RMSE), Nash Sutcliffe efficiency(NSE), and Standard Deviation(STDEV) were introduced for model assessment and sensitive parameters identification. The results showed that among all photosynthetic parameters only a small portion of parameters were sensitive, and the sensitive parameters were different across plant functional types: maximum rate of Rubisco activity(Vcmax25), maximum electron transport rate(Jmax25), triose phosphate use rate(TPU) and dark respiration in light(Rd) were sensitive in broad leafevergreen trees(BET), broad leaf-deciduous trees(BDT) and needle leaf-evergreen trees(NET), while only Vcmax25and TPU are sensitive in short vegetation(SV), dwarf trees and shrubs(DTS), and agriculture and grassland(AG). The two sensitivity analysis methods suggested a strong SA coherence;in contrast, different model performance metrics led to different SA results. This misfit suggests that more accurate values of sensitive parameters, specifically, species specific and seasonal variable parameters, are required to improve the performance of the FvCB model.
基金This work is supported in part by the Postdoctoral Science Foundation of China under Grant No.2020M683736in part by the Teaching reform project of higher education in Heilongjiang Province under Grant No.SJGY20210456in part by the Natural Science Foundation of Heilongjiang Province of China under Grant No.LH2021F038.
文摘The prediction of processor performance has important referencesignificance for future processors. Both the accuracy and rationality of theprediction results are required. The hierarchical belief rule base (HBRB)can initially provide a solution to low prediction accuracy. However, theinterpretability of the model and the traceability of the results still warrantfurther investigation. Therefore, a processor performance prediction methodbased on interpretable hierarchical belief rule base (HBRB-I) and globalsensitivity analysis (GSA) is proposed. The method can yield more reliableprediction results. Evidence reasoning (ER) is firstly used to evaluate thehistorical data of the processor, followed by a performance prediction modelwith interpretability constraints that is constructed based on HBRB-I. Then,the whale optimization algorithm (WOA) is used to optimize the parameters.Furthermore, to test the interpretability of the performance predictionprocess, GSA is used to analyze the relationship between the input and thepredicted output indicators. Finally, based on the UCI database processordataset, the effectiveness and superiority of the method are verified. Accordingto our experiments, our prediction method generates more reliable andaccurate estimations than traditional models.
基金The work was financially supported by Basic Public Welfare research Plan of Zhejiang Province(LGG19F030006)Key Laboratory of Intelligent Manufacturing Quality Big Data Tracing and Analysis of Zhejiang Province,China Jiliang University(Grant No.ZNZZSZ–CJLU2022–04)the Key Research and Development Program of Ningbo(2022Z165).
文摘The absorber is the key unit in the post-combustion monoethanolamine(MEA)-based carbon dioxide(CO_(2))capture process.A rate-based dynamic model for the absorber is developed and validated using steady-state experimental data reported in open literature.Sensitivity analysis is performed with respect to important model parameters associated with the reaction,mass transport and phy-sical property relationships.Then,a singular value decomposition(SVD)-based subspace parameter estimation method is proposed to improve the model accu-racy.Finally,dynamic simulations are carried out to investigate the effects of the feed rate of lean MEA solution and the flue inlet conditions.Simulation results indicate that the established dynamic model can reasonably reflect the physical behavior of the absorber.Some new insights are gained from the simulation results.
基金This work was supported by the National Natural Science Foundation of China(51774011)Funding Project of Anhui University of Science and Technology(QN2019115)Introduced Research Funding of Anhui University of Science and Technology(13190022).
文摘To study active heat insulation roadway in high temperature mines,the typical high temperature roadway of−965 m in Zhujidong Coal Mine of Anhui,China,is selected as prototype.The ANSYS numerical simulation method is used for sensitivity analysis of heat insulation layer with different thermal conductivity and thickness,as well as surrounding rock with different thermal conductivity and temperature on a heat-adjusting zone radius,surrounding rock temperature field and wall temperature.The results show that the heat-adjusting zone radius will entirely be in the right power index relationship to the ventilation time.Decrease in thermal conductivity and increase in thickness of insulation layer can effectively reduce the disturbance of airflow on the surrounding rock temperature,hence,beneficial for decreasing wall temperature.This favourable trend significantly decreases with ventilation time,increase in thermal conductivity and temperature of surrounding rock,heat-adjusting zone radius,surrounding rock temperature field,and wall temperature.Sensitivity analysis shows that the thermal physical properties of surrounding rock determine the temperature distribution of the roadway,hence,temperature of surrounding rock is considered as the most sensitive factor of all influencing factors.For the spray layer,thermal conductivity is more sensitive,compared to thickness.It is concluded that increase in the spray layer thickness is not as beneficial as using low thermal conductivity insulation material.Therefore,roadway preferential consideration should be given to the rocks with low temperature and thermal conductivity.The application of the insulation layer has positive significance for the thermal environment control in mine roadway,however,increase in the layer thickness without restriction has a limited effect on the thermal insulation.
基金jointly supported by the National Key R&D Program of China (2018YFB0605503)the National Natural Science Foundation of China (51804112)+2 种基金the National Key R&D Program of China (2018YFC0807801)the Open Foundation of Key Laboratory of Coal Exploration and Comprehensive Utilization of Ministry of Natural Resources (KF2021-5)the Natural Science Foundation of Hunan Province of China (2018JJ3169).
文摘To accelerate the achievement of China’s carbon neutrality goal and to study the factors affecting the geologic CO_(2)storage in the Ordos Basin,China’s National Key R&D Programs propose to select the Chang 6 oil reservoir of the Yanchang Formation in the Ordos Basin as the target reservoir to conduct the geologic carbon capture and storage(CCS)of 100000 t per year.By applying the basic theories of disciplines such as seepage mechanics,multiphase fluid mechanics,and computational fluid mechanics and quantifying the amounts of CO_(2)captured in gas and dissolved forms,this study investigated the effects of seven factors that influence the CO_(2)storage capacity of reservoirs,namely reservoir porosity,horizontal permeability,temperature,formation stress,the ratio of vertical to horizontal permeability,capillary pressure,and residual gas saturation.The results show that the sensitivity of the factors affecting the gas capture capacity of CO_(2)decreases in the order of formation stress,temperature,residual gas saturation,horizontal permeability,and porosity.Meanwhile,the sensitivity of the factors affecting the dissolution capture capacity of CO_(2)decreases in the order of formation stress,residual gas saturation,temperature,horizontal permeability,and porosity.The sensitivity of the influencing factors can serve as the basis for carrying out a reasonable assessment of sites for future CO_(2)storage areas and for optimizing the design of existing CO_(2)storage areas.The sensitivity analysis of the influencing factors will provide basic data and technical support for implementing geologic CO_(2)storage and will assist in improving geologic CO_(2)storage technologies to achieve China’s carbon neutralization goal.
基金This study was funded by the National Natural Science Foundation of China(grant number 41871279 and 41901364).
文摘Background:Process-based models are widely used to simulate forest productivity,but complex parameterization and calibration challenge the application and development of these models.Sensitivity analysis of numerous parameters is an essential step in model calibration and carbon flux simulation.However,parameters are not dependent on each other,and the results of sensitivity analysis usually vary due to different forest types and regions.Hence,global and representative sensitivity analysis would provide reliable information for simple calibration.Methods:To determine the contributions of input parameters to gross primary productivity(GPP)and net primary productivity(NPP),regression analysis and extended Fourier amplitude sensitivity testing(EFAST)were conducted for Biome-BGCMuSo to calculate the sensitivity index of the parameters at four observation sites under climate gradient from ChinaFLUX.Results:Generally,GPP and NPP were highly sensitive to C:Nleaf(C:N of leaves),Wint(canopy water interception coefficient),k(canopy light extinction coefficient),FLNR(fraction of leaf N in Rubisco),MRpern(coefficient of linear relationship between tissue N and maintenance respiration),VPDf(vapor pressure deficit complete conductance reduction),and SLA1(canopy average specific leaf area in phenological phase 1)at all observation sites.Various sensitive parameters occurred at four observation sites within different climate zones.GPP and NPP were particularly sensitive to FLNR,SLA1 and Wint,and C:Nleaf in temperate,alpine and subtropical zones,respectively.Conclusions:The results indicated that sensitivity parameters of China's forest ecosystems change with climate gradient.We found that parameter calibration should be performed according to plant functional type(PFT),and more attention needs to be paid to the differences in climate and environment.These findings contribute to determining the target parameters in field experiments and model calibration.
基金National Natural Science Foundation of China(Grant No.51922093)Scientific Research Fund of Zhejiang Provincial Education Department of China(Grant No.Y202148352)Major Science and Technology Projects in Ningbo of China(Grant No.2019B10054).
文摘As a type of hydraulic rotary actuator,a helical hydraulic rotary actuator exhibits a large angle,high torque,and compact structure;hence,it has been widely used in various fields.However,its core technology is proprietary to several companies and thus has not been disclosed.Furthermore,the relevant reports are primarily limited to the component level.The dynamic characteristics of the output when a helical rotary actuator is applied to a closed-loop system are investigated from the perspective of driving system design.Two main aspects are considered:one is to establish a reliable mathematical model and the other is to consider the effect of system parameter perturbation on the output.In this study,a detailed mechanical analysis of a helical rotary hydraulic cylinder is first performed,factors such as friction and load are considered,and an accurate dynamic model of the actuator is established.Subsequently,considering the nonlinear characteristics of pressure flow and the dynamic characteristics of the valve,a dynamic model of a valve-controlled helical rotary actuator angle closed-loop system is described based on sixth-order nonlinear state equations,which has never been reported previously.After deriving the system model,a sensitivity analysis of 23 main parameters in the model with a perturbation of 10%is performed under nine operating conditions.Finally,the system dynamics model and sensitivity analysis results are verified via a prototype experiment and co-simulation,which demonstrate the reliability of the theoretical results obtained in this study.The results provide an accurate mathematical model and analysis basis for the structural optimization or control compensation of similar systems.
基金Supported by the National Natural Science Foundation of China(10272109)
文摘In order to understand the effect of hardening ductility parameters and softening ductility parameters of the concrete damage plastic model in LS-DYNA,a sensitivity and reliability analysis of these parameters through a convenient cube unit test was conducted. The results showed that the peak strength strain was independent of the hardening ductility parameter DH,but affected by AH,BH,and CH. The softening ductility was mainly related to the softening ductility parameter AS,but not affected by the damage ductility exponent BS. In case that the model with default parameters failed to match the AS-controlled damage softening phase,an optimized model with an AS correction was developed. The corrected model with the AS value of 2 matched well with the code model,and exhibited good feasibility in predicting the stress-strain curve of different grades of concrete. Moreover,the practicability of the corrected model was further validated by the conventional triaxial test. The simulated curve exhibited favorable consistence with the trial curve. Therefore,the model with parameter correction could provide a prospective reference for predicting the mechanical properties of concrete.
文摘The groundwater constitutes the main source of drinking water for the populations in the Dabou region which is marked by a multiplication of socio-economic activities. The quality of groundwater is increasingly tested by diverse sources of pollution caused by these human activities. In order to preserve their quality against any form of contamination, the present study aims to assess the groundwater vulnerability in this region and to highlight the relative importance of hydrogeological parameters which will be taken into account in this assessment. The assessment of the intrinsic vulnerability is to identify the most sensitive zones in order to prevent the groundwater pollution risks on the surface of the ground. To do it, the DRASTIC method is applied through a GIS. The GIS has also used to perform sensitivity analysis through the map removal and the single-parameter sensitivity analysis tests. The indexes calculated for the DRASTIC vulnerability map vary from 95 to 187 of the North towards the South. This vulnerability map presents four classes: very high (26.22%) in the South and the East, high (37.71%) in the Center, the North-East and the North-West, moderate (34.73%) to the North and the West and low (1.34%) in the North. The DRASTIC vulnerability map is heavily influenced by the impact of vadose zone and the depth to water table according to the first test. For the second test, it is the impact of vadose zone, the aquifer media and the soil media which have a more significant impact on the vulnerability map. Both sensitivity analysis tests confirm that the impact of vadose zone therefore sediment type is more implied in this assessment of the groundwater vulnerability in the Dabou region.
