DSpace Angular :: Browsing by Author "Lira, Ignacio"

Browsing by Author "Lira, Ignacio"

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Assessing the Uncertainty in Transient Heat Conduction Within Large Plates, Long Cylinders, and Spheres
(TAYLOR & FRANCIS INC, 2012) Lira, Ignacio; Campo, Antonio
Relevant quantities in transient heat conduction within solids include the temperature distribution and the total energy released up to a given time. Expressions for these quantities are well known in the case of large plates, long cylinders, and spheres initially at a uniform temperature and subject to convective boundary conditions. Because the heat transfer coefficient usually is not known accurately, it is of interest to assess how the uncertainty associated with its estimated value propagates into the uncertainties of the local temperatures inside these three bodies and of the total energy released from them. In this paper a calculation procedure in agreement with current international recommendations is developed for this purpose.
Bayesian evaluation of comparison data
(2006) Lira, Ignacio
This paper develops a Bayesian procedure to evaluate comparison data when more than two participants measure independently a stable travelling standard. The procedure yields the analytic probability density function (pdf) that encodes the collective state of knowledge. From this pdf, the estimated value of the measurand may be derived numerically, together with its associated standard uncertainty and coverage interval. The pdfs for the degrees of equivalence of the participating laboratories can also be calculated.
Combining inconsistent data from interlaboratory comparisons
(2007) Lira, Ignacio
The most widely used procedure for finding the value of a quantity from data obtained from interlaboratory comparisons involves calculating the inverse-variance weighted mean of the laboratories' estimates. This method produces adequate results if the data are consistent. However, sometimes a consistency test reveals the possible existence of outliers that nevertheless have to be included in the evaluation task. In this paper the Bayesian understanding of probability is used to derive three methods that may be applied in the case when the data appear to be inconsistent. The performances of these methods are compared through a simulated example.
Comparison between the conventional and Bayesian approaches to evaluate measurement data
(2006) Lira, Ignacio; Woeger, Wolfgang
Measurement data subject only to random effects can be evaluated within the frameworks of conventional as well as Bayesian statistical theory. In this paper, both viewpoints are presented and examples including Gaussian, uniform and Poisson statistics are discussed. The cases of data produced by different observers, and of quantities expressed by measurement models involving systematic effects, are also briefly touched upon. It is shown that, although in most practical cases the uncertainty intervals obtained from repeated measurements using either theory may be similar, their interpretation is completely different. Since the Bayesian approach treats random and systematic effects in the same way, the authors claim that it is more flexible and better adapted to practice than conventional theory.
Coverage intervals according to MARLAP, Bayesian statistics and the new ISO 11929 for ionising radiation measurements
(PERGAMON-ELSEVIER SCIENCE LTD, 2012) Grientschnig, Dieter; Lira, Ignacio
The coverage intervals stipulated by ISO 11929 (2010) for estimating the uncertainty from ionising radiation measurements of replicate samples are compared with those of MARLAP (= Multi-Agency Radiological Laboratory Analytical Protocols Manual) and of Bayesian statistics. The latter two intervals agree well despite their different concepts. Whereas for either of them the ratio of the length of the coverage interval and MARLAP's standard uncertainty grows when the number of samples decreases, no such growth arises for the interval mandated by ISO 11929 (2010). It may therefore be too short (e.g. for three samples by a factor of approximately 2). (C) 2011 Elsevier Ltd. All rights reserved.
Interferometric measurement of a diffusion coefficient
(2007) Riquelme, Rodrigo; Lira, Ignacio; Perez-Lopez, Carlos; Rayas, Juan A.; Rodriguez-Vera, Ramon
Two methods to measure the diffusion coefficient of a species in a liquid by optical interferometry were compared. The methods were tested on a 1.75 M NaCl aqueous solution diffusing into water at 26 degrees C. Results were D = 1.587 x 10(-9) m(2) s(-1) with the first method and D = 1.602 x 10(-9) m(2) s(-1) with the second method. Monte Carlo simulation was used to assess the possible dispersion of these results. The standard uncertainties were found to be of the order of 0.05 x 10(-9) m(2) s(-1) with both methods. We found that the value of the diffusion coefficient obtained by either method is very sensitive to the magnification of the optical system, and that if diffusion is slow the measurement of time does not need to be very accurate.
Introducing scale analysis by way of a pendulum
(2007) Lira, Ignacio
Empirical correlations are a practical means of providing approximate answers to problems in physics whose exact solution is otherwise difficult to obtain. The correlations relate quantities that are deemed to be important in the physical situation to which they apply, and can be derived from experimental data by means of dimensional and/or scale analysis. These techniques are discussed through two examples. The first example involves determining the period of a pendulum, for which a simple yet very accurate correlation at arbitrary amplitudes of oscillation is derived. The second example refers to a more practical application, that of obtaining a heat transfer coefficient. In the appendix, the proposed correlation for the period of the pendulum is compared with other approximate formulae in the literature.
Motion of a red blood cell in interference field
(ELSEVIER, 2009) Alfredo Viera, Luis; Lira, Ignacio; Soto, Leopoldo; Pavez, Cristian
The motion of a red blood cell suspended in blood plasma in a two-beam plane interference Held was studied experimentally. A cw Argon Ion laser was used. A model is proposed to describe the observed motion. The model is based on a balance between the optical gradient force and the drag force, and yields the location of the cell as a function of time, starting from a stationary position at an arbitrary distance from a dark fringe until becoming trapped at the center of the closest bright fringe. it is suggested that the discrepancy between the predictions of the model and the observed motion is attributable to the influence of the wall close to which the cell flows. (C) 2008 Elsevier B.V. All rights reserved.
Non-informative priors in GUM Supplement 1
(ELSEVIER SCI LTD, 2011) Lira, Ignacio; Grientschnig, Dieter
Supplement 1 to the 'Guide to the Expression of Uncertainty in Measurement' (GUM S1) proposes a Monte Carlo method for the propagation of the probability density functions (PDFs) assigned to the input quantities that are related to an output quantity through a measurement model. Guidance is provided in GUM Si for assigning PDFs to the input quantities for which data but no prior knowledge are available. The procedure relies on Bayes' theorem and on the use of appropriate non-informative priors. An inconsistency in the choice of such priors is pointed out. (C) 2011 Elsevier Ltd. All rights reserved.
On the choice of a noninformative prior for Bayesian inference of discretized normal observations
(2012) Elster, Clemens; Lira, Ignacio
We consider the task of Bayesian inference of the mean of normal observations when the available data have been discretized and when no prior knowledge about the mean and the variance exists. An application is presented which illustrates that the discretization of the data should not be ignored when their variability is of the order of the discretization step. We show that the standard (noninformative) prior for location-scale family distributions is no longer appropriate. We work out the reference prior of Berger and Bernardo, which leads to different and more reasonable results. However, for this prior the posterior also shows some non-desirable properties. We argue that this is due to the inherent difficulty of the considered problem, which also affects other methods of inference. We therefore complement our analysis by an empirical Bayes approach. While such proceeding overcomes the disadvantages of the standard and reference priors and appears to provide a reasonable inference, it may raise conceptual concerns. We conclude that it is difficult to provide a widely accepted prior for the considered problem.
Probabilistic and least-squares inference of the parameters of a straight-line model
(2007) Lira, Ignacio; Elster, Clemens; Woeger, Wolfgang
Two methods are presented by which a straight line is to be fitted to a cloud of points in Cartesian coordinates. It is assumed that data are available in the form of a series of measurements in each coordinate, together with an assessment of their covariance matrices. In the first (probabilistic) method, the joint probability density function (PDF) for the two parameters of the straight line is considered. An explicit expression for this PDF is derived; it allows one to compute numerically the expectations, the variances and the covariance between the two parameters of the straight line. The second method is that of least-squares; it renders a non-linear system of equations for the point estimates of the parameters, as well as an approximation to their covariance matrix. In contrast to least-squares, the probabilistic method allows for the exact calculation of the probability that the true values of the parameters lie within specified intervals.
Reassessment of a calibration model by Bayesian reference analysis
(2011) Grientschnig, Dieter; Lira, Ignacio
The Bayesian analysis of a simple calibration model is reconsidered. Observed values are at hand that conform to a Gaussian probability distribution of unknown standard deviation S. The mean of this distribution is given by a polynomial function of the measurand Y. For the coefficients P of this polynomial a state-of-knowledge distribution is available, whereas no prior information about Y and S exists. A conditional reference prior for (Y, S) given P is derived. It shows no functional dependence on the measurand in the case that the calibration function is linear, but depends non-trivially on the measurand otherwise. This prior is compared with other priors that have been used in the literature to analyse the same calibration model. It leads to a different posterior distribution than the application of Supplement 1 to the 'Guide to the Expression of Uncertainty in Measurement'. An example illustrates differences of results founded on the various non-informative priors.
Resolution revisited
(2006) Lira, Ignacio
A simple procedure is presented to evaluate the standard uncertainty of a quantity about which discretized measurement data are available. The procedure is based on Bayesian statistics and depends on the value of the experimental variance. If the variance is less than a certain limit, the standard uncertainty can be obtained by the numerical approximations and plots provided in the paper. Otherwise, the data can be treated as if it were not resolution-limited.
Revision of 'Reassessment of a calibration model by Bayesian reference analysis'
(2012) Grientschnig, Dieter; Lira, Ignacio
In a previous paper (2011 Metrologia 48 L7-11) we have calculated a reference prior for a calibration model where a state-of-knowledge distribution of the coefficients of the calibration function is provided. Observed values of the response for a fixed value of the stimulus are also available. They are assumed to conform to a Gaussian probability distribution of unknown standard deviation. The calculation of the reference prior is revised here using a different sequence of subsets of the parameter space. This choice is preferable to the earlier one with respect to the properties of the ensuing posterior. In contrast to the former result the revised reference prior leads to the same posterior distribution as the application of Supplement 1 to the 'Guide to the Expression of Uncertainty in Measurement'.
Scales of free convection around a vertical cylinder
(2008) Lira, Ignacio
The natural scales of the laminar steady-state free convection flow regime surrounding an isothermal vertical cylinder are established. It is shown that nondimensionalizing the momentum and energy equations in terms of the Rayleigh or Boussinesq numbers allows the use of the Prandtl number as a criterion to establish whether the motive buoyancy force is mainly balanced by inertia or by friction. Instead, in the conventional formulation based on the Grashof number, this distinction is not possible.
Uncertainty associated with the energy content in flow measurement of natural gas including real-time correction for fluid properties
(2007) Martins, Lilian; Frota, Mauricio N.; Lira, Ignacio
A procedure is proposed to calculate the uncertainty of the energy content associated with real-time flow measurements of natural gas. The procedure was applied to a measuring scheme consisting of an arrangement of orifice plate meters installed in parallel, coupled to an on-line gas chromatograph and a real-time data processing flow computer. Two distinct sources of natural gas with appreciable fluctuations in chemical properties were considered. The analysis suggests that the uncertainty depends mainly on these fluctuations, on the flow regime and on systematic errors. The work also suggests that the chemical analysis-sampling rate plays an important role in the overall uncertainty budget.

Browsing by Author "Lira, Ignacio"

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