Uncertainty and sensitivity analysis of in-vessel phenomena under severe accident mitigation strategy based on ISAA-SAUP program

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.

On an isotropic porous solid cylinder:the analytical solution and sensitivity analysis of the pressure

Within this work,we perform a sensitivity analysis to determine the influence of the material input parameters on the pressure in an isotropic porous solid cylinder.We provide a step-by-step guide to obtain the analytical solution for a porous isotropic elastic cylinder in terms of the pressure,stresses,and elastic displacement.We obtain the solution by performing a Laplace transform on the governing equations,which are those of Biot's poroelasticity in cylindrical polar coordinates.We enforce radial boundary conditions and obtain the solution in the Laplace transformed domain before reverting back to the time domain.The sensitivity analysis is then carried out,considering only the derived pressure solution.This analysis finds that the time t,Biot's modulus M,and Poisson's ratio ν have the highest influence on the pressure whereas the initial value of pressure P_(0) plays a very little role.

A Bayesian multi-model inference methodology for imprecise momentindependent global sensitivity analysis of rock structures

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.

Explainable Neural Network for Sensitivity Analysis of Lithium-ion Battery Smart Production

Battery production is crucial for determining the quality of electrode,which in turn affects the manufactured battery performance.As battery production is complicated with strongly coupled intermediate and control parameters,an efficient solution that can perform a reliable sensitivity analysis of the production terms of interest and forecast key battery properties in the early production phase is urgently required.This paper performs detailed sensitivity analysis of key production terms on determining the properties of manufactured battery electrode via advanced data-driven modelling.To be specific,an explainable neural network named generalized additive model with structured interaction(GAM-SI)is designed to predict two key battery properties,including electrode mass loading and porosity,while the effects of four early production terms on manufactured batteries are explained and analysed.The experimental results reveal that the proposed method is able to accurately predict battery electrode properties in the mixing and coating stages.In addition,the importance ratio ranking,global interpretation and local interpretation of both the main effects and pairwise interactions can be effectively visualized by the designed neural network.Due to the merits of interpretability,the proposed GAM-SI can help engineers gain important insights for understanding complicated production behavior,further benefitting smart battery production.

Calculations and Sensitivity Analysis of Chlorine-,NO_(x)-,and Bromine-Depleting Cycles of Stratospheric Ozone

This paper presents an engineering system approach using a 2D model of conservation of mass to study the dynamics of ozone and concerned chemical species in the stratosphere.By considering all fourteen photolysis,ozone-generating,and-depleting chemical reactions,the model calculated the transient,spatial changes of ozone under different physical-chemical-radiative conditions.Validation against the measured data demonstrated good accuracy,close match of our model with the observed ozone concentrations at both 20°S and 90°N locations.The deviation in the average concentration was less than 1% and in ozone profiles less than 17%.The impacts of various chlorine-(Cl),nitrogen oxides-(NO_(x)),and bromine-(Br)depleting cycles on ozone concentrations and distribution were investigated.The chlorine catalytic depleting cycle was found to exhibit the most significant impact on ozone dynamics,confirming the key role of chlorine in the problem of ozone depletion.Sensitivity analysis was conducted with levels of 25%,50%,100%,200%,and 400% of the baseline value.The combined cycles(Cl+NO_(x)+Br)showed the most significant influence on ozone behavior.The total ozone abundance above the South Pole could decrease by a small 3%,from 281 DU(Dubson Units)to 273 DU for the 25% level,or by a huge thinning of 60%to 114 DU for the 400% concentration level.When the level of chlorine gases increased beyond 200%,it would cause ozone depletion to a level of ozone hole(below 220 DU).The 2D Ozone Model presented in this paper demonstrates robustness,convenience,efficiency,and executability for analyzing complex ozone phenomena in the stratosphere.

Sensitivity analysis for stochastic user equilibrium with elastic demand assignment model

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.

Separation of Comprehensive Geometrical Errors of a 3-DOF Parallel Manipulator Based on Jacobian Matrix and Its Sensitivity Analysis with Monte-Carlo Method

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.

Error Modeling and Sensitivity Analysis of a Parallel Robot with SCARA(Selective Compliance Assembly Robot Arm) Motions

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.

Nonlinear Mathematical Modeling and Sensitivity Analysis of Hydraulic Drive Unit

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.

Quantitative investigation on micro-parameters of cemented paste backfill and its sensitivity analysis

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.

Parameter identification and global sensitivity analysis of Xin'anjiang model using meta-modeling approach

Parameter identification, model calibration, and uncertainty quantification are important steps in the model-building process, and are necessary for obtaining credible results and valuable information. Sensitivity analysis of hydrological model is a key step in model uncertainty quantification, which can identify the dominant parameters, reduce the model calibration uncertainty, and enhance the model optimization efficiency. There are, however, some shortcomings in classical approaches, including the long duration of time and high computation cost required to quantitatively assess the sensitivity of a multiple-parameter hydrological model. For this reason, a two-step statistical evaluation framework using global techniques is presented. It is based on （1） a screening method （Morris） for qualitative ranking of parameters, and （2） a variance-based method integrated with a meta-model for quantitative sensitivity analysis, i.e., the Sobol method integrated with the response surface model （RSMSobol）. First, the Morris screening method was used to qualitatively identify the parameters＇ sensitivity, and then ten parameters were selected to quantify the sensitivity indices. Subsequently, the RSMSobol method was used to quantify the sensitivity, i.e., the first-order and total sensitivity indices based on the response surface model （RSM） were calculated. The RSMSobol method can not only quantify the sensitivity, but also reduce the computational cost, with good accuracy compared to the classical approaches. This approach will be effective and reliable in the global sensitivity analysis of a complex large-scale distributed hydrological model.

Seismic response comparison and sensitivity analysis of pile foundation in liquefiable and non-liquefiable soils

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.

Influence and sensitivity analysis of thermal parameters on temperature field distribution of active thermal insulated roadway in high temperature mine

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.

Finite element response sensitivity analysis of three-dimensional soil-foundation-structure interaction (SFSI) systems

The nonlinear finite element（FE） analysis has been widely used in the design and analysis of structural or geotechnical systems.The response sensitivities（or gradients） to the model parameters are of significant importance in these realistic engineering problems.However the sensitivity calculation has lagged behind,leaving a gap between advanced FE response analysis and other research hotspots using the response gradient.The response sensitivity analysis is crucial for any gradient-based algorithms,such as reliability analysis,system identification and structural optimization.Among various sensitivity analysis methods,the direct differential method（DDM） has advantages of computing efficiency and accuracy,providing an ideal tool for the response gradient calculation.This paper extended the DDM framework to realistic complicated soil-foundation-structure interaction（SFSI） models by developing the response gradients for various constraints,element and materials involved.The enhanced framework is applied to three-dimensional SFSI system prototypes for a pilesupported bridge pier and a pile-supported reinforced concrete building frame structure,subjected to earthquake loading conditions.The DDM results are verified by forward finite difference method（FFD）.The relative importance（RI） of the various material parameters on the responses of SFSI system are investigated based on the DDM response sensitivity results.The FFD converges asymptotically toward the DDM results,demonstrating the advantages of DDM（e.g.,accurate,efficient,insensitive to numerical noise）.Furthermore,the RI and effects of the model parameters of structure,foundation and soil materials on the responses of SFSI systems are investigated by taking advantage of the sensitivity analysis results.The extension of DDM to SFSI systems greatly broaden the application areas of the d gradient-based algorithms,e.g.FE model updating and nonlinear system identification of complicated SFSI systems.

Optimal topology design of replaceable bar dampers of a reticulated shell based on sensitivity analysis

In this study,a method for control of reticulated shells is proposed and its practicality is demonstrated.The control is implemented by replacing selected bars of the shell with passive viscoelastic dampers.By applying the eigenvalue perturbation technique and the earthquake spectrum concept,the sensitivities of various topologies of the shell are analyzed,and the optimal topology is determined by taking their symmetries into consideration.The results of this research show that common damper topologies are not effective for all types of responses and recorded earthquakes.The optimal topology identifi ed requires a minimal number of dampers for each type of earthquake record.The displacement control effect of the dynamic responses of the optimal topology is 10% – 20%; the acceleration control effect is also about 10% – 20%; and the axial force control effect is as much as 30% – 45%.Furthermore,the incremental dynamic analysis(IDA) method is used to investigate the stability of the controlled shell.The results show that the dynamic stability of the controlled shell is well preserved when it is vibrated under vibration and is better than the uncontrolled shell.The ultimate load increased by 10% and the elements entered into the plastic stage when the peak acceleration reached 580 Gal,which is 200 Gal larger than the uncontrolled shell.

Finite Element Model Updating of Bridge Structures Based on Sensitivity Analysis and Optimization Algorithm

The dynamic characteristics of bridge structures, such as the natural frequencies, mode shapes and model damping ratio, are the basis of structural dynamic computation, seismic analysis, vibration control and structural health condition monitoring. In this paper, a three-dimensional finite-element model is established for a highway bridge over a railway on No.312 National Highway and the ambient test is carried out in site, the dynamic characteristics of the bridge are studied using the finite-element analysis and ambient vibration measurements. Comparison between the theoretical and experimental results shows that the frequency differences of the modes range between 0.44% and 8.77%. If the measurement is more reliable, the finite element model updating is necessary. Thus, a set of design variables is selected based on sensitivity analysis, then the finite element model of the bridge is updated based on optimization algorithm. The results of model updating show that the proposed updating method in this paper is more simple and effective, the updated finite element model can reflect the dynamic characteristics of the bridge better, the analytical results can provide the theoretical basis for damage identification and health condition monitoring of the bridge.

Ranking environmental projects model based on multicriteria decision-making and the weight sensitivity analysis

With the fast growth of Chinese economic, more and more capital will be invested in environmental projects. How to select the environmental investment projects （alternatives） for obtaining the best environmental quality and economic benefits is an important problem for the decision makers. The purpose of this paper is to develop a decision-making model to rank a finite number of alternatives with several and sometimes conflicting criteria. A model for ranking the projects of municipal sewage treatment plants is proposed by using exports＇ information and the data of the real projects. And, the ranking result is given based on the PROMETHEE method. Furthermore, by means of the concept of the weight stability intervals （WSI）, the sensitivity of the ranking results to the size of criteria values and the change of weights value of criteria are discussed. The result shows that some criteria, such as “proportion of benefit to project cost”, will influence the ranking result of alternatives very strong while others not. The influence are not only from the value of criterion but also from the changing the weight of criterion. So, some criteria such as “proportion of benefit to project cost” are key critera for ranking the projects. Decision makers must be cautious to them.

Adjoint-based Sensitivity Analysis of a Mesoscale Low on the Mei-yu Front and Its Implications for Adaptive Observation

An adjoint sensitivity analysis of one mesoscale low on the mei-yu Front is presented in this paper. The sensitivity gradient of simulation error dry energy with respect to initial analysis is calculated. And after verifying the ability of a tangent linear and adjoint model to describe small perturbations in the nonlinear model, the sensitivity gradient analysis is implemented in detail. The sensitivity gradient with respect to different physical fields are not uniform in intensity, simulation error is most sensitive to the vapor mixed ratio. The localization and consistency are obvious characters of horizontal distribution of the sensitivity gradient, which is useful for the practical implementation of adaptive observation. The sensitivity region tilts to the northwest with height increasing; the singular vector calculation proves that this tilting characterizes a quick-growing structure, which denotes that using the leading singular vectors to decide the adaptive observation region is proper. When connected with simulation of a mesoscale low on the mei-yu Front, the sensitivity gradient has the following physical characters： the obvious sensitive region is mesoscale, concentrated in the middle-upper troposphere, and locates around the key system; and the sensitivity gradient of different physical fields correlates dynamically.

Global sensitivity analysis of the AquaCrop model for winter wheat under different water treatments based on the extended Fourier amplitude sensitivity test

Sensitivity analysis （SA） is an effective tool for studying crop models; it is an important link in model localization and plays an important role in crop model calibration and application. The objectives were to （i） determine influential and non-influential parameters with respect to above ground biomass （AGB）, canopy cover （CC）, and grain yield of winter wheat in the Beijing area based on the AquaCrop model under different water treatments （rainfall, normal irrigation, and over-irrigation）; and （ii） generate an AquaCrop model that can be used in the Beijing area by setting non-influential parameters to fixed values and adjusting influential parameters according to the SA results. In this study, field experiments were conducted during the 2012-2013,2013-2014, and 2014-2015 winter wheat growing seasons at the National Precision Agriculture Demonstration Research Base in Beijing, China. The extended Fourier amplitude sensitivity test （EFAST） method was used to perform SA of the AquaCrop model using 42 crop parameters, in order to verify the SA results, data from the 2013-2014 growing season were used to calibrate the AquaCrop model, and data from 2012-2013 and 2014-2015 growing seasons were val- idated. For AGB and yield of winter wheat, the total order sensitivity analysis had more sensitive parameters than the first order sensitivity analysis. For the AGB time-series, parameter sensitivity was changed under different water treatments; in comparison with the non-stressful conditions （normal irrigation and over-irrigation）, there were more sensitive parameters under water stress （rainfall）, while root development parameters were more sensitive. For CC with time-series and yield, there were more sensitive parameters under water stress than under no water stress. Two parameters sets were selected to calibrate the AquaCrop model, one group of parameters were under water stress, and the others were under no water stress, there were two more sensitive parameters （growing degree-days （GDD） from sowing to the maximum rooting depth （root） and the maximum effective rooting depth （rtx）） under water stress than under no water stress. The results showed that there was higher accuracy under water stress than under no water stress. This study provides guidelines for AquaCrop model calibration and application in Beijing, China, as well providing guidance to simplify the AquaCrop model and improve its precision, especially when many parameters are used.

Multi-parameter Sensitivity Analysis and Application Research in the Robust Optimization Design for Complex Nonlinear System

The current research of complex nonlinear system robust optimization mainly focuses on the features of design parameters, such as probability density functions, boundary conditions, etc. After parameters study, high-dimensional curve or robust control design is used to find an accurate robust solution. However, there may exist complex interaction between parameters and practical engineering system. With the increase of the number of parameters, it is getting hard to determine high-dimensional curves and robust control methods, thus it＇s difficult to get the robust design solutions. In this paper, a method of global sensitivity analysis based on divided variables in groups is proposed. By making relevant variables in one group and keeping each other independent among sets of variables, global sensitivity analysis is conducted in grouped variables and the importance of parameters is evaluated by calculating the contribution value of each parameter to the total variance of system response. By ranking the importance of input parameters, relatively important parameters are chosen to conduct robust design analysis of the system. By applying this method to the robust optimization design of a real complex nonlinear system-a vehicle occupant restraint system with multi-parameter, good solution is gained and the response variance of the objective function is reduced to 0.01, which indicates that the robustness of the occupant restraint system is improved in a great degree and the method is effective and valuable for the robust design of complex nonlinear system. This research proposes a new method which can be used to obtain solutions for complex nonlinear system robust design.