A sensitivity analysis of the PAWN sensitivity index

Soil moisture is one of the vital environmental variables in the land–atmosphere cycle. A study of the sensitivity analysis of bistatic scattering coefficients from bare soil at the Ku-band is presented, with the aim of deepening our understanding of the bistatic scattering features and exploring its potential in soil moisture retrieval. First, a well-established advanced integral method was adopted for simulating the bistatic scattering response of bare soil. Secondly, a sensitivity index and a normalized weight quality index were proposed to evaluate the effect of soil moisture on the bistatic scattering coefficient in terms of polarization and angular diversity, and the combinations thereof. The results of single-polarized VV data show that the regions with the maximum sensitivity and high quality index, simultaneously, to soil moisture are in the forward off-specular direction. However, due to the effect of surface roughness and surface autocorrelation function (ACF), the single-polarized data have some limitations for soil moisture inversion. By contrast, the results of two different polarization combinations, as well as a dual-angular simulation of one transmitter and two receivers, show significant estimation benefits. It can be seen that they all provide better ACF suppression capabilities, larger high-sensitivity area, and higher quality indices compared to single-polarized estimation. In addition, dual polarization or dual angular combined measurement provides the possibility of retrieving soil moisture in backward regions. These results are expected to contribute to the design of future bistatic observation systems.

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Intima heterogeneity in stress assessment of atherosclerotic plaques

Interface Focus ◽

10.1098/rsfs.2017.0008 ◽

2017 ◽

Vol 8 (1) ◽

pp. 20170008 ◽

Cited By ~ 5

Author(s):

Ali C. Akyildiz ◽

Lambert Speelman ◽

Bas van Velzen ◽

Raoul R. F. Stevens ◽

Antonius F. W. van der Steen ◽

...

Keyword(s):

Sensitivity Analysis ◽

Plaque Rupture ◽

Homogeneous Model ◽

Sensitivity Analyses ◽

Homogeneous Material ◽

Sensitivity Index ◽

Stress Assessment ◽

Heterogeneous Models ◽

Homogeneous Models ◽

Accuracy Stress

Atherosclerotic plaque rupture is recognized as the primary cause of cardiac and cerebral ischaemic events. High structural plaque stresses have been shown to strongly correlate with plaque rupture. Plaque stresses can be computed with finite-element (FE) models. Current FE models employ homogeneous material properties for the heterogeneous atherosclerotic intima. This study aimed to evaluate the influence of intima heterogeneity on plaque stress computations. Two-dimensional FE models with homogeneous and heterogeneous intima were constructed from histological images of atherosclerotic human coronaries ( n = 12). For homogeneous models, a single stiffness value was employed for the entire intima. For heterogeneous models, the intima was subdivided into four clusters based on the histological information and different stiffness values were assigned to the clusters. To cover the reported local intima stiffness range, 100 cluster stiffness combinations were simulated. Peak cap stresses (PCSs) from the homogeneous and heterogeneous models were analysed and compared. By using a global variance-based sensitivity analysis, the influence of the cluster stiffnesses on the PCS variation in the heterogeneous intima models was determined. Per plaque, the median PCS values of the heterogeneous models ranged from 27 to 160 kPa, and the PCS range varied between 43 and 218 kPa. On average, the homogeneous model PCS values differed from the median PCS values of heterogeneous models by 14%. A positive correlation ( R 2 = 0.72) was found between the homogeneous model PCS and the PCS range of the heterogeneous models. Sensitivity analysis showed that the highest main sensitivity index per plaque ranged from 0.26 to 0.83, and the average was 0.47. Intima heterogeneity resulted in substantial changes in PCS, warranting stress analyses with heterogeneous intima properties for plaque-specific, high accuracy stress assessment. Yet, computations with homogeneous intima assumption are still valuable to perform sensitivity analyses or parametric studies for testing the effect of plaque geometry on PCS. Moreover, homogeneous intima models can help identify low PCS, stable type plaques with thick caps. Yet, for thin cap plaques, accurate stiffness measurements of the clusters in the cap and stress analysis with heterogeneous cap properties are required to characterize the plaque stability.

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Parametric Sensitivity Analysis for Importance Measure on Failure Probability and Its Efficient Kriging Solution

Mathematical Problems in Engineering ◽

10.1155/2015/685826 ◽

2015 ◽

Vol 2015 ◽

pp. 1-13 ◽

Cited By ~ 2

Author(s):

Yishang Zhang ◽

Yongshou Liu ◽

Xufeng Yang

Keyword(s):

Sensitivity Analysis ◽

Failure Probability ◽

Computational Effort ◽

Importance Measure ◽

Sensitivity Index ◽

Reliability Engineering ◽

Parametric Sensitivity ◽

Distribution Parameters ◽

The Moment ◽

Sensitivity Indicator

The moment-independent importance measure (IM) on the failure probability is important in system reliability engineering, and it is always influenced by the distribution parameters of inputs. For the purpose of identifying the influential distribution parameters, the parametric sensitivity of IM on the failure probability based on local and global sensitivity analysis technology is proposed. Then the definitions of the parametric sensitivities of IM on the failure probability are given, and their computational formulae are derived. The parametric sensitivity finds out how the IM can be changed by varying the distribution parameters, which provides an important reference to improve or modify the reliability properties. When the sensitivity indicator is larger, the basic distribution parameter becomes more important to the IM. Meanwhile, for the issue that the computational effort of the IM and its parametric sensitivity is usually too expensive, an active learning Kriging (ALK) solution is established in this study. Two numerical examples and two engineering examples are examined to demonstrate the significance of the proposed parametric sensitivity index, as well as the efficiency and precision of the calculation method.

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Accuracy design of high precision machine tools using error sensitivity analysis methodology

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406216645625 ◽

2016 ◽

Vol 231 (18) ◽

pp. 3401-3413 ◽

Cited By ~ 1

Author(s):

Wenjie Tian ◽

Shaopeng Liu ◽

Xingxing Liu

Keyword(s):

Sensitivity Analysis ◽

Machine Tool ◽

Machine Tools ◽

Geometric Error ◽

Sensitivity Index ◽

Assembly Accuracy ◽

Machining Test ◽

Precision Machine Tools ◽

Design And Manufacture ◽

Source Errors

Geometric accuracy is a crucially important performance factor for machine tools. Theoretically, the effects of source errors on pose accuracy (positional and angular accuracy) of 3-, 4- or 5-axis machine tools cannot fully be compensated by software, and only those pose errors associated with the permission motions are compensatable by means of error compensation. Therefore, the uncompensatable pose errors should be strictly guaranteed in the processes of design and manufacture. In this paper, after the geometric error model is established, the source errors affecting the uncompensatable pose accuracy are identified out of all the source errors. In order to enhance the understanding of which source errors have more influences on the pose accuracy, a probabilistic sensitivity analysis method is proposed, and the global sensitivity index is defined to evaluate the influence in the overall workspace. According to the sensitivity analysis results, the uncompensatable pose accuracy index is allocated to each source error. And then, assembly accuracy acceptance criteria are proposed as a guideline for machine assemblers. As an application example, the presented approaches are applied to the accuracy design and manufacture of a 4-axis machine tool, and double ball bar measurement and machining test are carried out to check the accuracy of the designed machine tool.

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Sensitivity-guided evaluation of the HBV hydrological model parameterization

Journal of Hydroinformatics ◽

10.2166/hydro.2012.011 ◽

2012 ◽

Vol 15 (3) ◽

pp. 967-990 ◽

Cited By ~ 8

Author(s):

M. B. Zelelew ◽

K. Alfredsen

Keyword(s):

Sensitivity Analysis ◽

Hydrological Model ◽

River Basin Management ◽

Low Flow ◽

Model Parameters ◽

Sensitivity Index ◽

Analysis Method ◽

Flow Conditions ◽

Model Parameterization ◽

Sensitivity Analysis Method

Applying hydrological models for river basin management depends on the availability of the relevant data information to constrain the model residuals. The estimation of reliable parameter values for parameterized models is not guaranteed. Identification of influential model parameters controlling the model response variations either by main or interaction effects is therefore critical for minimizing model parametric dimensions and limiting prediction uncertainty. In this study, the Sobol variance-based sensitivity analysis method was applied to quantify the importance of the HBV conceptual hydrological model parameterization. The analysis was also supplemented by the generalized sensitivity analysis method to assess relative model parameter sensitivities in cases of negative Sobol sensitivity index computations. The study was applied to simulate runoff responses at twelve catchments varying in size. The result showed that varying up to a minimum of four to six influential model parameters for high flow conditions, and up to a minimum of six influential model parameters for low flow conditions can sufficiently capture the catchments' responses characteristics. To the contrary, varying more than nine out of 15 model parameters will not make substantial model performance changes on any of the case studies.

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Sensitivity analysis of the Chaohu Lake eutrophication model with a new index based on the Morris method

Water Science & Technology Water Supply ◽

10.2166/ws.2017.204 ◽

2017 ◽

Vol 18 (4) ◽

pp. 1375-1387 ◽

Cited By ~ 1

Author(s):

Yulin Wang ◽

Zulin Hua ◽

Liang Wang

Keyword(s):

Sensitivity Analysis ◽

Life Stage ◽

Eastern China ◽

Parameter Sensitivity ◽

Chaohu Lake ◽

Sensitivity Index ◽

Lake Eutrophication ◽

Multiple Model ◽

Morris Method ◽

Sensitivity Indices

Abstract Chaohu Lake is a large shallow lake in eastern China, and few eutrophication model studies have been conducted there. We present practical sensitivity indices based on the Morris method to compare the sensitivity of a parameter group on one model output with that of one parameter on multiple model outputs. The new sensitivity indices were employed to measure the parameter sensitivity of the Chaohu Lake eutrophication model. The results of the sensitivity analysis demonstrate that the most sensitive parameters on cyanobacteria biomass, NH4, NO3, and PO4 were BMR, KDN, Nitm, and KRP, and the most sensitive parameter groups were algae-related, nitrogen-related, and phosphorus-related, which all directly participate in their cycles. Furthermore, Nitm, KRP, KDN, KHP, BMR, KTB, KTHDR, and KTCOD were the most important for the Chaohu Lake eutrophication model. The water environment characteristics, such as the cyanobacteria life stage in the simulated period, significantly affected parameter sensitivity. The power-law relationship between the new sensitivity index and the standard deviation of model variables in the Chaohu Lake model were also determined. This finding allows us to estimate the interactions between parameters using their sensitivity index. The results provide a basis for further improvement of the Chaohu Lake eutrophication model.

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NUMERICAL ANALYSIS OF SMART STRUCTURES WITH UNCERTAINTIES

International Journal of Computational Methods ◽

10.1142/s0219876204000137 ◽

2004 ◽

Vol 01 (02) ◽

pp. 227-239 ◽

Cited By ~ 1

Author(s):

S. VALLIAPPAN ◽

C. K. CHEE

Keyword(s):

Sensitivity Analysis ◽

Finite Element ◽

Numerical Analysis ◽

Fuzzy Sets ◽

Numerical Method ◽

Smart Structures ◽

Sensitivity Index ◽

Material Parameters ◽

Element Technique ◽

Fuzzy Parameters

In this paper, a numerical method for the analysis of smart structures with uncertainties involved in the material parameters is presented. This method combines the finite element technique, concepts of fuzzy sets and optimization. For the optimization of fuzzy parameters, a sensitivity index is proposed. The sensitivity analysis based on the proposed sensitivity index can be effectively used to reduce the number of variables to be fuzzified and thus reducing the computational efforts considerably.

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Global Sensitivity Analysis for Stay Vane and Casing Design of Reaction Hydraulic Turbine

Volume 3A: Fluid Applications and Systems ◽

10.1115/ajkfluids2019-4684 ◽

2019 ◽

Author(s):

Hyunkyoo Cho ◽

Ujjwal Shrestha ◽

Young-Do Choi ◽

Jungwan Park

Keyword(s):

Sensitivity Analysis ◽

Design Process ◽

Performance Measures ◽

Global Sensitivity Analysis ◽

Computational Cost ◽

Surrogate Models ◽

Sensitivity Index ◽

Global Sensitivity ◽

Design Variables ◽

Hydraulic Turbines

Abstract Global sensitivity analysis (GSA) estimates influence of design variables in the entire design domain on performance measures. Hence, using GSA, important design variables could be found for an engineering application with high dimension which require computationally expensive analyses. Then, similar engineering applications could use selected variables to carry out design process with smaller dimension and affordable computational cost. In this study, GSA has been carried out for the performance measures in design of stay vane and casing of reaction hydraulic turbines. Global sensitivity index method is used for GSA because it can fully capture the effect of interaction between the design variables. For efficiency, genetic aggregation surrogate models are constructed using the responses of computational fluid dynamic (CFD) analysis. Global sensitivity indices for the performance measures of stay vane and casing have been evaluated using the surrogate models. It is found that less than three design variables among 12 are effective in the design process of stay vane and casing in reaction hydraulic turbines.

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A Performance Comprehension of Various Numerical Estimators for Variance-Based Sensitivity Analysis in Building Energy Simulations

Volume 1: 39th Computers and Information in Engineering Conference ◽

10.1115/detc2019-98490 ◽

2019 ◽

Author(s):

Rasool Koosha ◽

Fatemeh Shahsavari

Keyword(s):

Sensitivity Analysis ◽

Building Materials ◽

Computational Cost ◽

Residential Building ◽

Building Energy ◽

Energy Performance ◽

Test Case ◽

Sensitivity Index ◽

Energy Simulations ◽

High Level

Abstract In the building energy performance simulation, the uncertainty analysis (UA) couples to the sensitivity analysis (SA) to handle ever-existing uncertainties; induced by the sources of uncertainty including random occupants behavior and degradation of building materials over time. As a building simulation tool reaches to a high level of complexity, it becomes more challenging for the sensitivity analysis to deliver reliable outputs; thus the accuracy of the SA results substantially depends upon the number of sample sets or the type of analysis performed. This paper describes a variance-based SA tool integrated into a building Resistance-Capacitance (RC) thermal model. Then, for a hypothetical residential building test case, three distinct first-order sensitivity index simulators and three total sensitivity index simulators are implemented and compared in terms of the dependency of results on the sample size, i.e., the demand for the computational cost.

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Strategic Framework for Parameterization of Cell Culture Models

Processes ◽

10.3390/pr7030174 ◽

2019 ◽

Vol 7 (3) ◽

pp. 174

Author(s):

Pavlos Kotidis ◽

Cleo Kontoravdi

Keyword(s):

Experimental Data ◽

Cell Culture ◽

Sensitivity Analysis ◽

Goodness Of Fit ◽

Sampling Methods ◽

Model Parameters ◽

Sensitivity Index ◽

Cho Cell ◽

Culture Models ◽

Cell Culture Models

Global Sensitivity Analysis (GSA) is a technique that numerically evaluates the significance of model parameters with the aim of reducing the number of parameters that need to be estimated accurately from experimental data. In the work presented herein, we explore different methods and criteria in the sensitivity analysis of a recently developed mathematical model to describe Chinese hamster ovary (CHO) cell metabolism in order to establish a strategic, transferable framework for parameterizing mechanistic cell culture models. For that reason, several types of GSA employing different sampling methods (Sobol’, Pseudo-random and Scrambled-Sobol’), parameter deviations (10%, 30% and 50%) and sensitivity index significance thresholds (0.05, 0.1 and 0.2) were examined. The results were evaluated according to the goodness of fit between the simulation results and experimental data from fed-batch CHO cell cultures. Then, the predictive capability of the model was tested against four different feeding experiments. Parameter value deviation levels proved not to have a significant effect on the results of the sensitivity analysis, while the Sobol’ and Scrambled-Sobol’ sampling methods and a 0.1 significance threshold were found to be the optimum settings. The resulting framework was finally used to calibrate the model for another CHO cell line, resulting in a good overall fit. The results of this work set the basis for the use of a single mechanistic metabolic model that can be easily adapted through the proposed sensitivity analysis method to the behavior of different cell lines and therefore minimize the experimental cost of model development.

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