Parameter sensitivity analysis for a biochemically-based photosynthesis model

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.

Analysis of Additional Damping Control Strategy and Parameter Optimization for Improving Small Signal Stability of VSC-HVDC System

The voltage source converter based high voltage direct current(VSC-HVDC)system is based on voltage source converter,and its control system is more complex.Also affected by the fast control of power electronics,oscillation phenomenon in wide frequency domain may occur.To address the problem of small signal stability of the VSCHVDC system,a converter control strategy is designed to improve its small signal stability,and the risk of system oscillation is reduced by attaching a damping controller and optimizing the control parameters.Based on the modeling of the VSC-HVDC system,the general architecture of the inner and outer loop control of the VSCHVDC converter is established;and the damping controllers for DC control and AC control are designed in the phase-locked loop and the inner and outer loop control parts respectively;the state-space statemodel of the control system is established to analyze its performance.And the electromagnetic transient simulation model is built on the PSCAD/EMTDC simulation platform to verify the accuracy of the small signal model.The influence of the parameters of each control part on the stability of the system is summarized.The main control parts affecting stability are optimized for the phenomenon of oscillation due to changes in operation mode occurring on the AC side due to faults and other reasons,which effectively eliminates system oscillation and improves system small signal stability,providing a certain reference for engineering design.

Improved seismoacoustic analysis model and its application to source parameter inversion of near-surface small-yield chemical explosions

The seismoacoustic analysis method has broad potential applications to source parameter estimation for near-surface explosion events such as industrial explosions and terrorist attacks.In this study,current models were improved by modifying the acoustic model and adopting the Bayesian Markov-chain-Monte-Carlo inversion method.The source parameters of near-surface small-yield chemical explosions were analyzed via the improved seismoacoustic analysis model and by the estimation accuracy of seismoacoustic joint inversion.Estimation and analysis results showed that the improved seismoacoustic analysis model considered ground shock coupling and the impact of explosion products ejecting from the surface so that the improved acoustic impulse relation was more consistent with the measured data than the Ford impulse relation.It is suitable for deep-burial,shallow-burial,and near-surface aerial explosions.Furthermore,trade-off relationships were declined through the application of the improved model to source parameter inversion for near-surface small-yield chemical explosions,and source parameter estimation accuracy was improved.

Landslide dynamic process and parameter sensitivity analysis by discrete element method: the case of Turnoff Creek rock avalanche

The great diversity and complexity of geological hazards in terms of flowing materials,environment,triggering mechanisms and physical processes during the flow bring great difficulties to the numerical parameter selection for the discrete element method.In order to identity the significance of individual parameters on the landslides dynamic process and provide valuable contribution to the runout analysis of similar landslide,the dynamic process and associated microscopic mechanism of the Turnoff Creek rock avalanche in Canada are simulated.The present numerical results are compared with the field survey data and the results of depth-integrated continuum method.The final deposit range matches well with the field survey data.It is illustrated that the discrete element method is robust and feasible to capture the dynamic characteristics of large rock avalanche over a complex terrain.Besides,a new method to assess the landslide hazard level based on the discrete element method is proposed.According to the parameter sensitivity analysis,it is demonstrated that the basal friction coefficient and bond strength are essential to the final deposit while rolling coefficient and restitution coefficient have little effects on it.

Long-term deformation analysis of Shuibuya concrete face rockfill dam based on response surface method and improved genetic algorithm

Due to the size effects of rockfill materials, the settlement difference between numerical simulation and in situ monitoring of rockfill dams is a topic of general concern.The constitutive model parameters obtained from laboratory triaxial tests often underestimate the deformation of high rockfill dams.Therefore, constitutive model parameters obtained by back analysis were used to calculate and predict the long-term deformation of rockfill dams.Instead of using artificial neural networks (ANNs), the response surface method (RSM) was employed to replace the finite element simulation used in the optimization iteration.Only 27 training samples were required for RSM, improving computational efficiency compared with ANN, which required 300 training samples.RSM can be used to describe the relationship between the constitutive model parameters and dam settlements.The inversion results of the Shuibuya concrete face rockfill dam (CFRD) show that the calculated settlements agree with the measured data, indicating the accuracy and efficiency of RSM.

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.

Ranking parameters in urban energy models for various building forms and climates using sensitivity analysis

Urban Building Energy Modelling(UBEM)allows us to simulate buildings’energy performances at a larger scale.However,creating a reliable urban-scale energy model of new or existing urban areas can be difficult since the model requires overly detailed input data,which is not necessarily publicly unavailable.Model calibration is a necessary step to reduce the uncertainties and simulation results in order to develop a reliable and accurate UBEM.Due to the concerns over computational resources and the time needed for calibration,a sensitivity analysis is often required to identify the key parameters with the most substantial impact before the calibration is deployed in UBEM.Here,we study the sensitivity of uncertain input parameters that affect the annual heating and cooling energy demand by employing an urban-scale energy model,CitySim.Our goal is to determine the relative influence of each set of input parameters and their interactions on heating and cooling loads for various building forms under different climates.First,we conduct a global sensitivity analysis for annual cooling and heating consumption under different climate conditions.Building upon this,we investigate the changes in input sensitivity to different building forms,focusing on the indices with the largest Total-order sensitivity.Finally,we determine First-order indices and Total-order effects of each input parameter included in the urban building energy model.We also provide tables,showing the important parameters on the annual cooling and heating demand for each climate and each building form.We find that if the desired calibration process require to decrease the number of the inputs to save the computational time and cost,calibrating 5 parameters;temperature set-point,infiltration rate,floor U-value,avg.walls U-value and roof U-value would impact the results over 55%for any climate and any building form.

State dependent parameter method for importance analysis in the presence of epistemic and aleatory uncertainties

For the structure system with epistemic and aleatory uncertainties,a new state dependent parameter(SDP) based method is presented for obtaining the importance measures of the epistemic uncertainties.By use of the marginal probability density function(PDF) of the epistemic variable and the conditional PDF of the aleatory one at the fixed epistemic variable,the epistemic and aleatory uncertainties are propagated to the response of the structure firstly in the presented method.And the computational model for calculating the importance measures of the epistemic variables is established.For solving the computational model,the high efficient SDP method is applied to estimating the first order high dimensional model representation(HDMR) to obtain the importance measures.Compared with the direct Monte Carlo method,the presented method can considerably improve computational efficiency with acceptable precision.The presented method has wider applicability compared with the existing approximation method,because it is suitable not only for the linear response functions,but also for nonlinear response functions.Several examples are used to demonstrate the advantages of the presented method.

Parameter Identification for Static Var Compensator Model Using Sensitivity Analysis and Improved Whale Optimization Algorithm

A parameter estimation method based on an improved Whale Optimization Algorithm is proposed in this paper to identify the parameters of a static var compensator(SVC)model.First,a mathematical model of SVC is established.Then,the reverse learning strategy and Levy flight disturbance strategy are introduced to improve the whale optimization algorithm,and the improved whale optimization algorithm is applied to the parameter identification of the static var compensator model.Finally,a stepwise identification method,by analyzing the local sensitivities of parameters,is proposed which solves the problem of low accuracy caused by multi-parameter identification.This method provides a new estimation strategy for accurately identifying the parameters of the static var compensator model.Estimation results show that the parameter estimation method can be an effective tool to solve the problem of parameter identification for the SVC model.

Parametric sensitivity analysis of precipitation and temperature based on multi-uncertainty quantification methods in the Weather Research and Forecasting model

Sensitivity analysis(SA) has been widely used to screen out a small number of sensitive parameters for model outputs from all adjustable parameters in weather and climate models, helping to improve model predictions by tuning the parameters. However, most parametric SA studies have focused on a single SA method and a single model output evaluation function, which makes the screened sensitive parameters less comprehensive. In addition, qualitative SA methods are often used because simulations using complex weather and climate models are time-consuming. Unlike previous SA studies, this research has systematically evaluated the sensitivity of parameters that affect precipitation and temperature simulations in the Weather Research and Forecasting(WRF) model using both qualitative and quantitative global SA methods. In the SA studies, multiple model output evaluation functions were used to conduct various SA experiments for precipitation and temperature. The results showed that five parameters(P3, P5, P7, P10, and P16) had the greatest effect on precipitation simulation results and that two parameters(P7 and P10) had the greatest effect for temperature. Using quantitative SA, the two-way interactive effect between P7 and P10 was also found to be important, especially for precipitation. The microphysics scheme had more sensitive parameters for precipitation, and P10(the multiplier for saturated soil water content) was the most sensitive parameter for both precipitation and temperature. From the ensemble simulations, preliminary results indicated that the precipitation and temperature simulation accuracies could be improved by tuning the respective sensitive parameter values, especially for simulations of moderate and heavy rain.

不同降水驱动的SWAT模型参数不确定性研究

以抚河流域与黑河流域为研究区,应用4种降水产品(CMORPH CMA、CMFD、CMADS、MSWEP)驱动SWAT模型模拟日流量,评估4种降水产品在湿润区与干旱区的适用性;使用自适应降维评估法选出流域的敏感参数,并进行一致性检验。结果表明:抚河流域4种降水产品的纳什效率系数(NSE)均在0.70以上,其中CMORPH CMA和CMADS的NSE均能达到0.82;黑河流域CMORPH CMA和CMADS的NSE大于等于0.76,而CMFD和MSWEP的NSE分别为0.72和0.74。抚河流域4种降水产品具有相同的敏感参数;黑河流域CMORPH CMA和CMADS有相同的6个敏感参数,而CMFD和MSWEP则分别有5个和8个敏感参数。4种降水产品在湿润流域和干旱流域都能得到较好的应用效果,但是CMORPH CMA和CMADS的模拟效果要优于CMFD和MSWEP。不同的降水输入也会对模型参数敏感性分析的结果产生影响,当降水表现越接近时,所筛选的敏感性参数也越相似。

上海地区基坑开挖数值分析中土体HS-Small模型参数的研究

数值分析方法已成为分析敏感环境下基坑开挖对环境影响的最重要手段,其关键是选择合适的土体本构模型和计算参数。HS-Small模型可以同时考虑土体剪切硬化和压缩硬化,而且还可以考虑土体剪切模量在微小应变范围内随应变衰减的行为,因此,HS-Small模型在基坑开挖数值分析中具有很好的适用性。但HS-Small模型的参数较多,不仅包含了HS模型的参数,还包含了小应变参数,因此,获取完整的HS-Small模型参数存在一定困难。通过上海地区5个基坑开挖数值分析的实例对基于室内试验得出的上海典型土层HS模型参数进行了检验。通过参数的敏感性分析,对HS-Small模型的部分参数的确定方法进行了修正。在此基础上,采用反分析法确定了敏感性最强的小应变参数,从而初步完整地获取了上海典型土层土体HS-Small模型参数。采用文中确定的上海典型土层HS-Small模型参数对该地区若干典型基坑工程实例进行计算,结果表明,计算值与实测值吻合得较好,从而验证了确定的上海典型土层HS-Small模型参数的适用性。

厦门地区典型地层HS-small模型小应变参数敏感性分析

小应变硬化模型(HS-small模型)是以HS模型为基础提出的一种能反应土体小应变特性的本构模型,除了包含HS模型参数外,还包含两个小应变参数和,可以反映土体在小应变状态下呈现高度的非线性、高模量等特性。为了研究小应变参数对深基坑数值分析结果的敏感性,针对厦门地区典型土层,采用HS-small模型,通过有限元模拟某深基坑工程的施工过程,开展小应变参数对地表沉降及围护墙弯矩的敏感度分析,并研究参数随基坑开挖的演化规律。结果表明:在厦门地区在深基坑数值分析中,取值对地表沉降和围护墙弯矩值的影响较大,的取值影响相对小;粉质黏土和残积砂质黏性土的小应变参数对结果起到重要的影响;前期开挖,粉质黏土起控制作用,后期开挖,残积砂质黏性土起控制作用。

基于APSIM模型的旱地小麦叶面积指数相关参数敏感性分析及优化

为解决作物模型参数率定过程中参数众多导致的敏感参数定位迟缓和调参效率低的问题,本研究运用敏感性分析和智能优化算法相结合的方法对作物模型参数进行调整,以甘肃省定西市安定区李家堡镇麻子川村(2002—2004年)和凤翔镇安家沟村(2015—2017年)大田旱地小麦试验数据(叶面积指数)为参照,利用扩展傅里叶幅度检验法(EFAST),对APSIM-Wheat旱地小麦叶片生长子模型的23个参数进行敏感性分析,得到对模型结果较敏感的部分参数,然后利用粒子群优化算法对部分敏感参数进行优化。结果表明:1)影响旱地小麦叶片生长最敏感的参数依次为叶面积指数为0时最大比叶面积、叶片生长的氮限制因子、出苗到拔节积温、消光系数、拔节到开花积温、蒸腾效率系数;2)旱地小麦叶片生长子模型的参数优化结果:叶面积指数为0时最大比叶面积为26652 mm^(2)∙g^(−1),叶片生长的氮限制因子为0.96,出苗到拔节积温为382℃·d,消光系数为0.44,拔节到开花积温为542℃·d,蒸腾效率系数为0.0056;3)上述参数优化后的叶面积指数实测值与模拟值之间的均方根误差平均值从参数优化前的0.080减小到0.042,归一化均方根误差平均值从11.54%减小到6.11%,模型有效性指数平均值从0.962增加到0.988,优化后叶面积指数的模拟更好。该方法相对于传统的手工试错法,避免了优化参数的不确定性,实现参数自动率定,提高模型参数的率定效率,有利于模型快速地本地化应用,并指导农业生产。本研究方法也对APSIMWheat模型中其他作物模块的参数调整优化具有指导意义。

饱和土不排水柱孔扩张计算的通用半解析解

基于修正剑桥模型建立的不排水柱孔扩张解答仅适用于正常固结和弱超固结饱和黏土,不适用于严重超固结土和颗粒材料。采用统一状态参数模型(CASM)和Rowe剪胀方程推导土的弹塑性应力应变关系,结合大应变理论并引入辅助变量,用拉格朗日分析法推导了弹塑性土体有效应力和超孔隙水压力的相似解,在此基础上结合弹塑性区的边界条件,最终建立通用的饱和土中不排水柱孔扩张半解析解。计算结果表明,选择合适的间距比和应力-状态参数,所得结果与修正剑桥模型结果一致,并且对严重超固结土的计算结果更加合理;通过修正参数取值,该半解析解可用于更多类别饱和土中的不排水柱孔扩张计算。

基于HS-Small本构模型的银川地区深基坑开挖-降水过程数值分析

针对银川地区缺乏数值计算深基坑稳定性和锚杆受力等相关研究,运用midas GTS NX软件中HS-Small本构模型,对采取锚钉支护的宁夏自治区银川某地下车库深基坑开挖-地下水位下降过程进行了数值分析。结果表明:随着基坑的开挖,基坑边坡的变形量逐渐增大,最终位移最大值出现在基坑顶部阳角处;锚杆轴力随开挖深度的增加而加大,控制变形能力与所处位置有关,下部锚杆控制变形能力优于上部锚杆,锚钉联合支护形式和土钉墙支护形式界面处变形差异较大;随着开挖和持续降水,周边建筑物沉降缓慢增加且最终沉降小于警戒值;锚钉支护中土钉轴力表现为轻微S型曲线,最大值约位于沿土钉长度3/4位置处;通过模拟结果与实测数据进行了对比分析,两者吻合较好,反分析获得银川地区典型土层HS-Small模型的参数取值,可作为银川地区类似深基坑工程数值模拟的依据。

基于协同优化的耐压柱壳多学科多目标优化

为提高耐压柱壳的设计效率和结构性能,本文基于多学科设计优化思想,进行了耐压柱壳多学科设计优化的学科分解,确定了耐压柱壳多学科优化设计的设计参数,明确了设计变量间的耦合关系,设计了耐压柱壳参数化分析流程,进行了设计变量灵敏度分析。在利用响应面模型建立了具有较高拟合精度耐压柱壳近似模型的基础上,以质量排水量比和极限载荷为目标函数,建立了基于协同优化方法的耐压柱壳多学科多目标优化模型,在确定了系统层和学科层的优化求解方法基础上,设计了基于协同优化的耐压柱壳多学科多目标优化框架,进行了优化的求解工作,得到了优化方案。与初始方案的对比表明:所得到的Pareto解集中,部分方案在2个目标函数上均得到了优化,验证了优化框架的有效性。

小应变土体硬化模型参数的敏感性分析及确定方法

小应变土体硬化(hardening soil model with small strain stiffness,HSS)模型能够反映土体小应变阶段的非线性特性和应力相关性,在深基坑工程领域已被广泛应用。但由于模型参数众多,目前对参数确定方法尚缺乏系统研究。分析了HSS模型各参数的意义及常规确定方法,采用数值模拟方法开展了HSS模型参数的敏感性分析,基于统计的大量研究成果,建立了土体参数与孔隙比之间的非线性关系,进一步通过2处深基坑工程的变形分析进行验证。结果表明:在基坑数值分析中,参考动剪切模量G_(0)^(ref)的敏感性最高,参考切线模量E_(oed)^(ref)的敏感性最低,建立的非线性关系能够较好地反映土体模量与孔隙比的相关性,围护结构侧移的计算值及实测值较为吻合,验证了提出的参数确定方法的适用性,可为相关工程提供参考。

基于阻抗分析的无刷双馈独立发电系统控制参数设计方法

无刷双馈电机由于其高可靠性在独立发电应用中优势显著,然而特殊的电机结构亦导致控制参数设计更复杂。针对常用闭环函数法即使辅以强大的计算机软件,其分析结果仍含有大量干扰信息,不便于判定系统稳定情况的问题,本文充分借鉴双馈并网系统的阻抗分析思路,提出一种无刷双馈独立发电系统的控制参数设计方法。通过分别建立机侧、荷侧阻抗模型,避免信息过度集中而增加建模复杂程度,进而以工况变化下系统稳定为核心指标,基于广义奈奎斯特稳定判据对关键电流环参数进行设计。由于反映系统稳定情况的奈奎斯特曲线与(-1, j0)相对关系不受阻抗模型复杂程度影响,本文所提控制参数设计方法无需人工简化干预,可充分发挥计算机软件的智能优势。最后,在次/超同步满载等典型工况下,基于无刷双馈独立发电仿真及实验系统验证了所得控制参数的有效性,可保证工况改变时系统稳定发电并维持较好性能。

EB胶印机中心压印滚筒动力学特性研究

EB胶印技术是从根源上解决包装印刷业中污染问题的绿色印刷方式,中心滚筒是卫星式EB胶印机核心部件之一,为整机振动的主要来源,其动态特性直接影响着印品质量及生产效率。因此本文以卫星式EB胶印机中心滚筒为研究对象进行了动力学特性研究:首先建立中心压印滚筒的轴承-转子系统动力学微分方程;其次,研究不同参数对转子系统振动特性以及稳定性的影响规律;最后,研究中心滚筒内外壁之间的循环冷却水对滚筒结构造成的影响。其研究结果为EB胶印机中心滚筒的故障诊断、结构优化及稳定性分析提供了理论依据。