Multi-method global sensitivity analysis (MMGSA) for modelling floodplain hydrological processes

When studying hydrological processes with a numerical model, global sensitivity analysis (GSA) is essential if one is to understand the impact of model parameters and model formulation on results. However, different definitions of sensitivity can lead to a difference in the ranking of importance of the different model factors. Here we combine a fuzzy performance function with different methods of calculating global sensitivity to perform a multi-method global sensitivity analysis (MMGSA). We use an application of a finite element subsurface flow model (ESTEL-2D) on a flood inundation event on a floodplain of the River Severn to illustrate this new methodology. We demonstrate the utility of the method for model understanding and show how the prediction of state variables, such as Darcian velocity vectors, can be affected by such a MMGSA. This paper is a first attempt to use GSA with a numerically intensive hydrological model

Improvement and sensitivity analysis of thermal thin-ice thickness retrievals

Considering the sea ice decline in the Arctic during the last decades, polynyas are of high research interest since these features are core areas of new ice formation. The determination of ice formation requires accurate retrieval of polynya area and thin-ice thickness (TIT) distribution within the polynya.We use an established energy balance model to derive TITs with MODIS ice surface temperatures (Ts) and NCEP/DOE Reanalysis II in the Laptev Sea for two winter seasons. Improvements of the algorithm mainly concern the implementation of an iterative approach to calculate the atmospheric flux components taking the atmospheric stratification into account. Furthermore, a sensitivity study is performed to analyze the errors of the ice thickness. The results are the following: 1) 2-m air temperatures (Ta) and Ts have the highest impact on the retrieved ice thickness; 2) an overestimation of Ta yields smaller ice thickness errors as an underestimation of Ta; 3) NCEP Ta shows often a warm bias; and 4) the mean absolute error for ice thicknesses up to 20 cm is ±4.7 cm. Based on these results, we conclude that, despite the shortcomings of the NCEP data (coarse spatial resolution and no polynyas), this data set is appropriate in combination with MODIS Ts for the retrieval of TITs up to 20 cm in the Laptev Sea region. The TIT algorithm can be applied to other polynya regions and to past and future time periods. Our TIT product is a valuable data set for verification of other model and remote sensing ice thickness data.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Sensitivity analysis for transient stability studies

The paper presents a method for security control of electric power systems effected by generation reallocation, determined by sensitivity analysis and optimisation. The model is developed considering the dynamic aspects of the network (transient stability). Security control methodology is developed using sensitivity analysis of the security margin in relation to the mechanical power of synchronous machines in the system. The power reallocated to each machine is determined by means of linear programming. To illustrate the proposed methodology, an example is presented which considers a multimachine system composed of 10 synchronous machines, 45 buses, and 72 transmission lines, based on the configuration of a southern Brazilian system.

Reactive Control for Transmission Overload Relief Based on Sensitivity Analysis and Cooperative Game Theory

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Rotor support stiffness estimation by sensitivity analysis

In the present work, a method for rotor support stiffness estimation via a model updating process using the sensitivity analysis is presented. This method consists in using the eigenvalues sensitivity analysis, relating to the rotor support stiffnesses variation to perform the adjustment of the model based on the minimization of the difference between eigenvalues of reference and eigenvalues obtained via mathematical model from previously adopted support bearing stiffness values. The mathematical model is developed by the finite element method and the method of adjustment should converge employing an iterative process. The performance and robustness of the method have been analyzed through a numerical example.

Sensitivity analysis for overload-relief in transmission lines using an implicitly coupled method (CRIC)

The restructuring of energy markets to provide free access to the networks and the consequent increase of the number of power transactions has been causing congestions in transmission systems. As consequence, the networks suffer overloads in a more frequent way. One parameter that has strong influence on transfer capability is the reactive power flow. A sensitivity analysis can be used to find the best solution to minimize the reactive power flows and relief, the overload in one transmission line. The proposed methodology consists on the computation of two sensitivities based on the use of the Lc matrix from CRIC (Constant Reactive Implicitly Coupled) power flow method, that provide a set of actions to reduce the reactive power flow and alleviate overloads in the lines: (a) sensitivity between reactive power flow in lines and reactive power injections in the buses, (b) sensitivity between reactive power flow in lines and transformer's taps. © 2006 IEEE.

Structural reforms and economic growth in Latin America: a sensitivity analysis

Includes bibliography

Chaos control and sensitivity analysis of a double pendulum arm excited by an RLC circuit based nonlinear shaker

In this paper the dynamical interactions of a double pendulum arm and an electromechanical shaker is investigated. The double pendulum is a three degree of freedom system coupled to an RLC circuit based nonlinear shaker through a magnetic field, and the capacitor voltage is a nonlinear function of the instantaneous electric charge. Numerical simulations show the existence of chaotic behavior for some regions in the parameter space and this behaviour is characterized by power spectral density and Lyapunov exponents. The bifurcation diagram is constructed to explore the qualitative behaviour of the system. This kind of electromechanical system is frequently found in robotic systems, and in order to suppress the chaotic motion, the State-Dependent Riccati Equation (SDRE) control and the Nonlinear Saturation control (NSC) techniques are analyzed. The robustness of these two controllers is tested by a sensitivity analysis to parametric uncertainties.

Multiobjective engineering design optimization problems: a sensitivity analysis approach

This paper proposes two new approaches for the sensitivity analysis of multiobjective design optimization problems whose performance functions are highly susceptible to small variations in the design variables and/or design environment parameters. In both methods, the less sensitive design alternatives are preferred over others during the multiobjective optimization process. While taking the first approach, the designer chooses the design variable and/or parameter that causes uncertainties. The designer then associates a robustness index with each design alternative and adds each index as an objective function in the optimization problem. For the second approach, the designer must know, a priori, the interval of variation in the design variables or in the design environment parameters, because the designer will be accepting the interval of variation in the objective functions. The second method does not require any law of probability distribution of uncontrollable variations. Finally, the authors give two illustrative examples to highlight the contributions of the paper.

Parametric Sensitivity Analysis of the Most Recent Computational Models of Rabbit Cardiac Pacemaking

The cellular basis of cardiac pacemaking activity, and specifically the quantitative contributions of particular mechanisms, is still debated. Reliable computational models of sinoatrial nodal (SAN) cells may provide mechanistic insights, but competing models are built from different data sets and with different underlying assumptions. To understand quantitative differences between alternative models, we performed thorough parameter sensitivity analyses of the SAN models of Maltsev & Lakatta (2009) and Severi et al (2012). Model parameters were randomized to generate a population of cell models with different properties, simulations performed with each set of random parameters generated 14 quantitative outputs that characterized cellular activity, and regression methods were used to analyze the population behavior. Clear differences between the two models were observed at every step of the analysis. Specifically: (1) SR Ca2+ pump activity had a greater effect on SAN cell cycle length (CL) in the Maltsev model; (2) conversely, parameters describing the funny current (If) had a greater effect on CL in the Severi model; (3) changes in rapid delayed rectifier conductance (GKr) had opposite effects on action potential amplitude in the two models; (4) within the population, a greater percentage of model cells failed to exhibit action potentials in the Maltsev model (27%) compared with the Severi model (7%), implying greater robustness in the latter; (5) confirming this initial impression, bifurcation analyses indicated that smaller relative changes in GKr or Na+-K+ pump activity led to failed action potentials in the Maltsev model. Overall, the results suggest experimental tests that can distinguish between models and alternative hypotheses, and the analysis offers strategies for developing anti-arrhythmic pharmaceuticals by predicting their effect on the pacemaking activity.

Sensitivity analysis of a parabolic-elliptic problem

We consider the heat flux through a domain with subregions in which the thermal capacity approaches zero. In these subregions the parabolic heat equation degenerates to an elliptic one. We show the well-posedness of such parabolic-elliptic differential equations for general non-negative L-infinity-capacities and study the continuity of the solutions with respect to the capacity, thus giving a rigorous justification for modeling a small thermal capacity by setting it to zero. We also characterize weak directional derivatives of the temperature with respect to capacity as solutions of related parabolic-elliptic problems.

High sensitivity analysis of BRAF mutations in neoplastic and non-neoplastic thyroid lesions

The clonal distribution of BRAFV600E in papillary thyroid carcinoma (PTC) has been recently debated. No information is currently available about precursor lesions of PTCs. My first aim was to establish whether the BRAFV600E mutation occurs as a subclonal event in PTCs. My second aim was to screen BRAF mutations in histologically benign tissue of cases with BRAFV600E or BRAFwt PTCs in order to identify putative precursor lesions of PTCs. Highly sensitive semi-quantitative methods were used: Allele Specific LNA quantitative PCR (ASLNAqPCR) and 454 Next-Generation Sequencing (NGS). For the first aim 155 consecutive formalin-fixed and paraffin-embedded (FFPE) specimens of PTCs were analyzed. The percentage of mutated cells obtained was normalized to the estimated number of neoplastic cells. Three groups of tumors were identified: a first had a percentage of BRAF mutated neoplastic cells > 80%; a second group showed a number of BRAF mutated neoplastic cells < 30%; a third group had a distribution of BRAFV600E between 30-80%. The large presence of BRAFV600E mutated neoplastic cell sub-populations suggests that BRAFV600E may be acquired early during tumorigenesis: therefore, BRAFV600E can be heterogeneously distributed in PTC. For the second aim, two groups were studied: one consisted of 20 cases with BRAFV600E mutated PTC, the other of 9 BRAFwt PTCs. Seventy-five and 23 histologically benign FFPE thyroid specimens were analyzed from the BRAFV600E mutated and BRAFwt PTC groups, respectively. The screening of BRAF mutations identified BRAFV600E in “atypical” cell foci from both groups of patients. “Unusual” BRAF substitutions were observed in histologically benign thyroid associated with BRAFV600E PTCs. These mutations were very uncommon in the group with BRAFwt PTCs and in BRAFV600E PTCs. Therefore, lesions carrying BRAF mutations may represent “abortive” attempts at cancer development: only BRAFV600E boosts neoplastic transformation to PTC. BRAFV600E mutated “atypical foci” may represent precursor lesions of BRAFV600E mutated PTCs.

Studio di Flow-Assurance e sensitivity analysis in sistemi di distribuzione di petrolio e gas naturale

Argomento del lavoro è stato lo studio di problemi legati alla Flow-Asurance. In particolare, si focalizza su due aspetti: i) una valutazione comparativa delle diverse equazioni di stato implementate nel simulatore multifase OLGA, per valutare quella che porta a risultati più conservativi; ii) l’analisi della formazione di idrati, all’interno di sistemi caratterizzati dalla presenza di gas ed acqua. Il primo argomento di studio nasce dal fatto che per garantire continuità del flusso è necessario conoscere il comportamento volumetrico del fluido all’interno delle pipelines. Per effettuare tali studi, la Flow-Assurance si basa sulle Equazioni di Stato cubiche. In particolare, sono state confrontate: -L’equazione di Soave-Redlich-Kwong; -L’equazione di Peng-Robinson; -L’equazione di Peng-Robinson modificata da Peneloux. Sono stati analizzati 4 fluidi idrocarburici (2 multifase, un olio e un gas) con diverse composizioni e diverse condizioni di fase. Le variabili considerate sono state pressione, temperatura, densità e viscosità; sono state poi valutate le perdite di carico, parametro fondamentale nello studio del trasporto di un fluido, valutando che l'equazione di Peng-Robinson è quella più adatta per caratterizzare termodinamicamente il fluido durante una fase di design, in quanto fornisce l'andamento più conservativo. Dopo aver accertato la presenza di idrati nei fluidi multifase, l’obiettivo del lavoro è stato analizzare come il sistema rispondesse all’aggiunta di inibitori chimici per uscire dalla regione termodinamica di stabilità dell’idrato. Gli inibitori utilizzati sono stati metanolo e mono-etilen-glicole in soluzione acquosa. L’analisi è stata effettuata confrontando due metodi: -Metodo analitico di Hammerschmidt; -Metodo iterativo con PVTSim. I risultati ottenuti hanno dimostrato che entrambi gli inibitori utilizzati risolvono il problema della formazione di idrato spostando la curva di stabilità al di fuori delle pressioni e temperature che si incontrano nella pipeline. Valutando le quantità da iniettare, il metodo di Hammerschmidt risulta quello più conservativo, indicando portate maggiori rispetto al PVTsim, soprattutto aggiungendo metanolo.

Sensitivity Analysis for the Assessment of Causal Vaccine Effects on Viral Load in HIV Vaccine Trials

Vaccines with limited ability to prevent HIV infection may positively impact the HIV/AIDS pandemic by preventing secondary transmission and disease in vaccine recipients who become infected. To evaluate the impact of vaccination on secondary transmission and disease, efficacy trials assess vaccine effects on HIV viral load and other surrogate endpoints measured after infection. A standard test that compares the distribution of viral load between the infected subgroups of vaccine and placebo recipients does not assess a causal effect of vaccine, because the comparison groups are selected after randomization. To address this problem, we formulate clinically relevant causal estimands using the principal stratification framework developed by Frangakis and Rubin (2002), and propose a class of logistic selection bias models whose members identify the estimands. Given a selection model in the class, procedures are developed for testing and estimation of the causal effect of vaccination on viral load in the principal stratum of subjects who would be infected regardless of randomization assignment. We show how the procedures can be used for a sensitivity analysis that quantifies how the causal effect of vaccination varies with the presumed magnitude of selection bias.