936 resultados para Parametric sensitivity analysis
Resumo:
Potential parameters sensitivity analysis for helium unlike molecules, HeNe, HeAr, HeKr and HeXe is the subject of this work. Number of bound states these rare gas dimers can support, for different angular momentum, will be presented and discussed. The variable phase method, together with the Levinson's theorem, is used to explore the quantum scattering process at very low collision energy using the Tang and Toennies potential. These diatomic dimers can support a bound state even for relative angular momentum equal to five, as in HeXe. Vibrational excited states, with zero angular momentum, are also possible for HeKr and HeXe. Results from sensitive analysis will give acceptable order of magnitude on potentials parameters.
Parametric Sensitivity Analysis of the Most Recent Computational Models of Rabbit Cardiac Pacemaking
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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.
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We address under what conditions a magma generated by partial melting at 100 km depth in the mantle wedge above a subduction zone can reach the crust in dikes before stalling. We also address under what conditions primitive basaltic magma (Mg # >60) can be delivered from this depth to the crust. We employ linear elastic fracture mechanics with magma solidification theory and perform a parametric sensitivity analysis. All dikes are initiated at a depth of 100 km in the thermal core of the wedge, and the Moho is fixed at 35 km depth. We consider a range of melt solidus temperatures (800-1100 degrees C), viscosities (10-100 Pa s), and densities (2400-2700 kg m(-3)). We also consider a range of host rock fracture toughness values (50-300 MPa m(1/2)) and dike lengths (2-5 km) and two thermal structures for the mantle wedge (1260 and 1400 degrees C at 100 km depth and 760 and 900 degrees C at 35 km depth). For the given parameter space, many dikes can reach the Moho in less than a few hundred hours, well within the time constraints provided by U series isotope disequilibria studies. Increasing the temperature in the mantle wedge, or increasing the dike length, allows additional dikes to propagate to the Moho. We conclude that some dikes with vertical lengths near their critical lengths and relatively high solidus temperatures will stall in the mantle before reaching the Moho, and these may be returned by corner flow to depths where they can melt under hydrous conditions. Thus, a chemical signature in arc lavas suggesting partial melting of slab basalts may be partly influenced by these recycled dikes. Alternatively, dikes with lengths well above their critical lengths can easily deliver primitive magmas to the crust, particularly if the mantle wedge is relatively hot. Dike transport remains a viable primary mechanism of magma ascent in convergent tectonic settings, but the potential for less rapid mechanisms making an important contribution increases as the mantle temperature at the Moho approaches the solidus temperature of the magma.
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Purpose – Curve fitting from unordered noisy point samples is needed for surface reconstruction in many applications -- In the literature, several approaches have been proposed to solve this problem -- However, previous works lack formal characterization of the curve fitting problem and assessment on the effect of several parameters (i.e. scalars that remain constant in the optimization problem), such as control points number (m), curve degree (b), knot vector composition (U), norm degree (k), and point sample size (r) on the optimized curve reconstruction measured by a penalty function (f) -- The paper aims to discuss these issues -- Design/methodology/approach - A numerical sensitivity analysis of the effect of m, b, k and r on f and a characterization of the fitting procedure from the mathematical viewpoint are performed -- Also, the spectral (frequency) analysis of the derivative of the angle of the fitted curve with respect to u as a means to detect spurious curls and peaks is explored -- Findings - It is more effective to find optimum values for m than k or b in order to obtain good results because the topological faithfulness of the resulting curve strongly depends on m -- Furthermore, when an exaggerate number of control points is used the resulting curve presents spurious curls and peaks -- The authors were able to detect the presence of such spurious features with spectral analysis -- Also, the authors found that the method for curve fitting is robust to significant decimation of the point sample -- Research limitations/implications - The authors have addressed important voids of previous works in this field -- The authors determined, among the curve fitting parameters m, b and k, which of them influenced the most the results and how -- Also, the authors performed a characterization of the curve fitting problem from the optimization perspective -- And finally, the authors devised a method to detect spurious features in the fitting curve -- Practical implications – This paper provides a methodology to select the important tuning parameters in a formal manner -- Originality/value - Up to the best of the knowledge, no previous work has been conducted in the formal mathematical evaluation of the sensitivity of the goodness of the curve fit with respect to different possible tuning parameters (curve degree, number of control points, norm degree, etc.)
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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.
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This paper presents studies of cases in power systems by Sensitivity Analysis (SA) oriented by Optimal Power Flow (OPF) problems in different operation scenarios. The studies of cases start from a known optimal solution obtained by OPF. This optimal solution is called base case, and from this solution new operation points may be evaluated by SA when perturbations occur in the system. The SA is based on Fiacco`s Theorem and has the advantage of not be an iterative process. In order to show the good performance of the proposed technique tests were carried out on the IEEE 14, 118 and 300 buses systems. (C) 2010 Elsevier Ltd. All rights reserved.
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This paper presents a new approach to the transmission loss allocation problem in a deregulated system. This approach belongs to the set of incremental methods. It treats all the constraints of the network, i.e. control, state and functional constraints. The approach is based on the perturbation of optimum theorem. From a given optimal operating point obtained by the optimal power flow the loads are perturbed and a new optimal operating point that satisfies the constraints is determined by the sensibility analysis. This solution is used to obtain the allocation coefficients of the losses for the generators and loads of the network. Numerical results show the proposed approach in comparison to other methods obtained with well-known transmission networks, IEEE 14-bus. Other test emphasizes the importance of considering the operational constraints of the network. And finally the approach is applied to an actual Brazilian equivalent network composed of 787 buses, and it is compared with the technique used nowadays by the Brazilian Control Center. (c) 2007 Elsevier Ltd. All rights reserved.
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In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.
Resumo:
In studies assessing the effects of a given exposure variable and a specific outcome of interest, confusion may arise from the mistaken impression that the exposure variable is producing the outcome of interest, when in fact the observed effect is due to an existing confounder. However, quantitative techniques are rarely used to determine the potential influence of unmeasured confounders. Sensitivity analysis is a statistical technique that allows to quantitatively measuring the impact of an unmeasured confounding variable on the association of interest that is being assessed. The purpose of this study was to make it feasible to apply two sensitivity analysis methods available in the literature, developed by Rosenbaum and Greenland, using an electronic spreadsheet. Thus, it can be easier for researchers to include this quantitative tool in the set of procedures that have been commonly used in the stage of result validation.
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High speed trains, when crossing regions with abrupt changes in vertical stiffness of the track and/or subsoil, may generate excessive ground and track vibrations. There is an urgent need for specific analyses of this problem so as to allow reliable esimates of vibration amplitude. Full understanding of these phenomena will lead to new construction solutions and mitigation of undesirable features. In this paper analytical transient solutions of dynamic response of one-dimensional systems with sudden change of foundation stiffness are derived. Results are expressed in terms of vertical displacement. Sensitivity analysis of the response amplitude is also performed. The analytical expressions presented herein, to the authors’ knowledge, have not been published yet. Although related to one-dimensional cases, they can give useful insight into the problem. Nevertheless, in order to obtain realistic response, vehicle- rail interaction cannot be omitted. Results and conclusions are confirmed using general purpose commercial software ANSYS. In conclusion, this work contributes to a better understanding of the additional vibration phenomenon due to vertical stiffness variation, permitting better control of the train velocity and optimization of the track design.
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In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.
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We conduct a sensitivity analysis of several estimators related to household income, to explore how some details of the definitions of the variables concerned influence the values of the common estimates, such as the mean, median and (poverty) rates. The purpose of this study is to highlight that some of the operational definitions entail an element of arbitrariness which leaves an undesirable stamp on the inferences made. The analyses use both a cross-sectional and a longitudinal (panel) component of the EU-SILC database.
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This paper analyses the impact of using different correlation assumptions between lines of business when estimating the risk-based capital reserve, the Solvency Capital Requirement (SCR), under Solvency II regulations. A case study is presented and the SCR is calculated according to the Standard Model approach. Alternatively, the requirement is then calculated using an Internal Model based on a Monte Carlo simulation of the net underwriting result at a one-year horizon, with copulas being used to model the dependence between lines of business. To address the impact of these model assumptions on the SCR we conduct a sensitivity analysis. We examine changes in the correlation matrix between lines of business and address the choice of copulas. Drawing on aggregate historical data from the Spanish non-life insurance market between 2000 and 2009, we conclude that modifications of the correlation and dependence assumptions have a significant impact on SCR estimation.
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A mathematical model is proposed to analyze the effects of acquired immunity on the transmission of schistosomiasis in the human host. From this model the prevalence curve dependent on four parameters can be obtained. These parameters were estimated fitting the data by the maximum likelihood method. The model showed a good retrieving capacity of real data from two endemic areas of schistosomiasis: Touros, Brazil (Schistosoma mansoni) and Misungwi, Tanzania (S. haematobium). Also, the average worm burden per person and the dispersion of parasite per person in the community can be obtained from the model. In this paper, the stabilizing effects of the acquired immunity assumption in the model are assessed in terms of the epidemiological variables as follows. Regarded to the prevalence curve, we calculate the confidence interval, and related to the average worm burden and the worm dispersion in the community, the sensitivity analysis (the range of the variation) of both variables with respect to their parameters is performed.
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To estimate the possible direct effect of birth weight on blood pressure, it is conventional to condition on the mediator, current weight. Such conditioning can induce bias. Our aim was to assess the potential biasing effect of U, an unmeasured common cause of current weight and blood pressure, on the estimate of the controlled direct effect of birth weight on blood pressure, with the help of sensitivity analyses. We used data from a school-based study conducted in Switzerland in 2005-2006 (n = 3,762; mean age = 12.3 years). A small negative association was observed between birth weight and systolic blood pressure (linear regression coefficient βbw = -0.3 mmHg/kg, 95% confidence interval: -0.9, 0.3). The association was strengthened upon adjustment for current weight (βbw|C = -1.5 mmHg/kg, 95% confidence interval: -2.1, -0.9). Sensitivity analyses revealed that the negative conditional association was explained by U only if U was relatively strongly associated with blood pressure and if there was a large difference in the prevalence of U between low-birth weight and normal-birth weight children. This weakens the hypothesis that the negative relationship between birth weight and blood pressure arises only from collider-stratification bias induced by conditioning on current weight.