893 resultados para Uncertain parameters
Resumo:
The integrated Safety Assessment (ISA) methodology, developed by the Spanish Nuclear Safety Council (CSN), has been applied to a thermal-hydraulic analysis of PWR Station Blackout (SBO) sequences in the context of the IDPSA (Integrated Deterministic-Probabilistic Safety Assessment) network objectives. The ISA methodology allows obtaining the damage domain (the region of the uncertain parameters space where the damage limit is exceeded) for each sequence of interest as a function of the operator actuations times. Given a particular safety limit or damage limit, several data of every sequence are necessary in order to obtain the exceedance frequency of that limit. In this application these data are obtained from the results of the simulations performed with MAAP code transients inside each damage domain and the time-density probability distributions of the manual actions. Damage limits that have been taken into account within this analysis are: local cladding damage (PCT>1477 K); local fuel melting (T>2499 K); fuel relocation in lower plenum and vessel failure. Therefore, to every one of these damage variables corresponds a different damage domain. The operation of the new passive thermal shutdown seals developed by several companies since Fukushima accident is considered in the paper. The results show the capability and necessity of the ISA methodology, or similar, in order to obtain accurate results that take into account time uncertainties.
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La metodología Integrated Safety Analysis (ISA), desarrollada en el área de Modelación y Simulación (MOSI) del Consejo de Seguridad Nuclear (CSN), es un método de Análisis Integrado de Seguridad que está siendo evaluado y analizado mediante diversas aplicaciones impulsadas por el CSN; el análisis integrado de seguridad, combina las técnicas evolucionadas de los análisis de seguridad al uso: deterministas y probabilistas. Se considera adecuado para sustentar la Regulación Informada por el Riesgo (RIR), actual enfoque dado a la seguridad nuclear y que está siendo desarrollado y aplicado en todo el mundo. En este contexto se enmarcan, los proyectos Safety Margin Action Plan (SMAP) y Safety Margin Assessment Application (SM2A), impulsados por el Comité para la Seguridad de las Instalaciones Nucleares (CSNI) de la Agencia de la Energía Nuclear (NEA) de la Organización para la Cooperación y el Desarrollo Económicos (OCDE) en el desarrollo del enfoque adecuado para el uso de las metodologías integradas en la evaluación del cambio en los márgenes de seguridad debidos a cambios en las condiciones de las centrales nucleares. El comité constituye un foro para el intercambio de información técnica y de colaboración entre las organizaciones miembro, que aportan sus propias ideas en investigación, desarrollo e ingeniería. La propuesta del CSN es la aplicación de la metodología ISA, especialmente adecuada para el análisis según el enfoque desarrollado en el proyecto SMAP que pretende obtener los valores best-estimate con incertidumbre de las variables de seguridad que son comparadas con los límites de seguridad, para obtener la frecuencia con la que éstos límites son superados. La ventaja que ofrece la ISA es que permite el análisis selectivo y discreto de los rangos de los parámetros inciertos que tienen mayor influencia en la superación de los límites de seguridad, o frecuencia de excedencia del límite, permitiendo así evaluar los cambios producidos por variaciones en el diseño u operación de la central que serían imperceptibles o complicados de cuantificar con otro tipo de metodologías. La ISA se engloba dentro de las metodologías de APS dinámico discreto que utilizan la generación de árboles de sucesos dinámicos (DET) y se basa en la Theory of Stimulated Dynamics (TSD), teoría de fiabilidad dinámica simplificada que permite la cuantificación del riesgo de cada una de las secuencias. Con la ISA se modelan y simulan todas las interacciones relevantes en una central: diseño, condiciones de operación, mantenimiento, actuaciones de los operadores, eventos estocásticos, etc. Por ello requiere la integración de códigos de: simulación termohidráulica y procedimientos de operación; delineación de árboles de sucesos; cuantificación de árboles de fallos y sucesos; tratamiento de incertidumbres e integración del riesgo. La tesis contiene la aplicación de la metodología ISA al análisis integrado del suceso iniciador de la pérdida del sistema de refrigeración de componentes (CCWS) que genera secuencias de pérdida de refrigerante del reactor a través de los sellos de las bombas principales del circuito de refrigerante del reactor (SLOCA). Se utiliza para probar el cambio en los márgenes, con respecto al límite de la máxima temperatura de pico de vaina (1477 K), que sería posible en virtud de un potencial aumento de potencia del 10 % en el reactor de agua a presión de la C.N. Zion. El trabajo realizado para la consecución de la tesis, fruto de la colaboración de la Escuela Técnica Superior de Ingenieros de Minas y Energía y la empresa de soluciones tecnológicas Ekergy Software S.L. (NFQ Solutions) con el área MOSI del CSN, ha sido la base para la contribución del CSN en el ejercicio SM2A. Este ejercicio ha sido utilizado como evaluación del desarrollo de algunas de las ideas, sugerencias, y los algoritmos detrás de la metodología ISA. Como resultado se ha obtenido un ligero aumento de la frecuencia de excedencia del daño (DEF) provocado por el aumento de potencia. Este resultado demuestra la viabilidad de la metodología ISA para obtener medidas de las variaciones en los márgenes de seguridad que han sido provocadas por modificaciones en la planta. También se ha mostrado que es especialmente adecuada en escenarios donde los eventos estocásticos o las actuaciones de recuperación o mitigación de los operadores pueden tener un papel relevante en el riesgo. Los resultados obtenidos no tienen validez más allá de la de mostrar la viabilidad de la metodología ISA. La central nuclear en la que se aplica el estudio está clausurada y la información relativa a sus análisis de seguridad es deficiente, por lo que han sido necesarias asunciones sin comprobación o aproximaciones basadas en estudios genéricos o de otras plantas. Se han establecido tres fases en el proceso de análisis: primero, obtención del árbol de sucesos dinámico de referencia; segundo, análisis de incertidumbres y obtención de los dominios de daño; y tercero, cuantificación del riesgo. Se han mostrado diversas aplicaciones de la metodología y ventajas que presenta frente al APS clásico. También se ha contribuido al desarrollo del prototipo de herramienta para la aplicación de la metodología ISA (SCAIS). ABSTRACT The Integrated Safety Analysis methodology (ISA), developed by the Consejo de Seguridad Nuclear (CSN), is being assessed in various applications encouraged by CSN. An Integrated Safety Analysis merges the evolved techniques of the usually applied safety analysis methodologies; deterministic and probabilistic. It is considered as a suitable tool for assessing risk in a Risk Informed Regulation framework, the approach under development that is being adopted on Nuclear Safety around the world. In this policy framework, the projects Safety Margin Action Plan (SMAP) and Safety Margin Assessment Application (SM2A), set up by the Committee on the Safety of Nuclear Installations (CSNI) of the Nuclear Energy Agency within the Organization for Economic Co-operation and Development (OECD), were aimed to obtain a methodology and its application for the integration of risk and safety margins in the assessment of the changes to the overall safety as a result of changes in the nuclear plant condition. The committee provides a forum for the exchange of technical information and cooperation among member organizations which contribute their respective approaches in research, development and engineering. The ISA methodology, proposed by CSN, specially fits with the SMAP approach that aims at obtaining Best Estimate Plus Uncertainty values of the safety variables to be compared with the safety limits. This makes it possible to obtain the exceedance frequencies of the safety limit. The ISA has the advantage over other methods of allowing the specific and discrete evaluation of the most influential uncertain parameters in the limit exceedance frequency. In this way the changes due to design or operation variation, imperceptibles or complicated to by quantified by other methods, are correctly evaluated. The ISA methodology is one of the discrete methodologies of the Dynamic PSA framework that uses the generation of dynamic event trees (DET). It is based on the Theory of Stimulated Dynamics (TSD), a simplified version of the theory of Probabilistic Dynamics that allows the risk quantification. The ISA models and simulates all the important interactions in a Nuclear Power Plant; design, operating conditions, maintenance, human actuations, stochastic events, etc. In order to that, it requires the integration of codes to obtain: Thermohydraulic and human actuations; Even trees delineation; Fault Trees and Event Trees quantification; Uncertainty analysis and risk assessment. This written dissertation narrates the application of the ISA methodology to the initiating event of the Loss of the Component Cooling System (CCWS) generating sequences of loss of reactor coolant through the seals of the reactor coolant pump (SLOCA). It is used to test the change in margins with respect to the maximum clad temperature limit (1477 K) that would be possible under a potential 10 % power up-rate effected in the pressurized water reactor of Zion NPP. The work done to achieve the thesis, fruit of the collaborative agreement of the School of Mining and Energy Engineering and the company of technological solutions Ekergy Software S.L. (NFQ Solutions) with de specialized modeling and simulation branch of the CSN, has been the basis for the contribution of the CSN in the exercise SM2A. This exercise has been used as an assessment of the development of some of the ideas, suggestions, and algorithms behind the ISA methodology. It has been obtained a slight increase in the Damage Exceedance Frequency (DEF) caused by the power up-rate. This result shows that ISA methodology allows quantifying the safety margin change when design modifications are performed in a NPP and is specially suitable for scenarios where stochastic events or human responses have an important role to prevent or mitigate the accidental consequences and the total risk. The results do not have any validity out of showing the viability of the methodology ISA. Zion NPP was retired and information of its safety analysis is scarce, so assumptions without verification or approximations based on generic studies have been required. Three phases are established in the analysis process: first, obtaining the reference dynamic event tree; second, uncertainty analysis and obtaining the damage domains; third, risk quantification. There have been shown various applications of the methodology and advantages over the classical PSA. It has also contributed to the development of the prototype tool for the implementation of the ISA methodology (SCAIS).
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El accidente de pérdida de refrigerante (LOCA) en un reactor nuclear es uno de los accidentes Base de Diseño más preocupantes y estudiados desde el origen del uso de la tecnología de fisión en la industria productora de energía. El LOCA ocupa, desde el punto de vista de los análisis de seguridad, un lugar de vanguardia tanto en el análisis determinista (DSA) como probabilista (PSA), cuya diferenciada perspectiva ha ido evolucionando notablemente en lo que al crédito a la actuación de las salvaguardias y las acciones del operador se refiere. En la presente tesis se aborda el análisis sistemático de de las secuencias de LOCA por pequeña y mediana rotura en diferentes lugares de un reactor nuclear de agua a presión (PWR) con fallo total de Inyección de Seguridad de Alta Presión (HPSI). Tal análisis ha sido desarrollado en base a la metodología de Análisis Integrado de Seguridad (ISA), desarrollado por el Consejo de Seguridad Nuclear (CSN) y consistente en la aplicación de métodos avanzados de simulación y PSA para la obtención de Dominios de Daño, que cuantifican topológicamente las probabilidades de éxito y daño en función de determinados parámetros inciertos. Para la elaboración de la presente tesis, se ha hecho uso del código termohidráulico TRACE v5.0 (patch 2), avalado por la NRC de los EEUU como código de planta para la simulación y análisis de secuencias en reactores de agua ligera (LWR). Los objetivos del trabajo son, principalmente: (1) el análisis exhaustivo de las secuencias de LOCA por pequeña-mediana rotura en diferentes lugares de un PWR de tres lazos de diseño Westinghouse (CN Almaraz), con fallo de HPSI, en función de parámetros de gran importancia para los transitorios, tales como el tamaño de rotura y el tiempo de retraso en la respuesta del operador; (2) la obtención y análisis de los Dominios de Daño para transitorios de LOCA en PWRs, de acuerdo con la metodología ISA; y (3) la revisión de algunos de los resultados genéricos de los análisis de seguridad para secuencias de LOCA en las mencionadas condiciones. Los resultados de la tesis abarcan tres áreas bien diferenciadas a lo largo del trabajo: (a) la fenomenología física de las secuencias objeto de estudio; (b) las conclusiones de los análisis de seguridad practicados a los transitorios de LOCA; y (c) la relevancia de las consecuencias de las acciones humanas por parte del grupo de operación. Estos resultados, a su vez, son de dos tipos fundamentales: (1) de respaldo del conocimiento previo sobre el tipo de secuencias analizado, incluido en la extensa bibliografía examinada; y (2) hallazgos en cada una de las tres áreas mencionadas, no referidos en la bibliografía. En resumidas cuentas, los resultados de la tesis avalan el uso de la metodología ISA como método de análisis alternativo y sistemático para secuencias accidentales en LWRs. ABSTRACT The loss of coolant accident (LOCA) in nuclear reactors is one of the most concerning and analized accidents from the beginning of the use of fission technology for electric power production. From the point of view of safety analyses, LOCA holds a forefront place in both Deterministic (DSA) and Probabilistic Safety Analysis (PSA), which have significantly evolved from their original state in both safeguard performance credibility and human actuation. This thesis addresses a systematic analysis of small and medium LOCA sequences, in different places of a nuclear Pressurized Water Reactor (PWR) and with total failure of High Pressure Safety Injection (HPSI). Such an analysis has been grounded on the Integrated Safety Assessment (ISA) methodology, developed by the Spanish Nuclear Regulatory Body (CSN). ISA involves the application of advanced methods of simulation and PSA for obtaining Damage Domains that topologically quantify the likelihood of success and damage regarding certain uncertain parameters.TRACE v5.0 (patch 2) code has been used as the thermalhydraulic simulation tool for the elaboration of this work. Nowadays, TRACE is supported by the US NRC as a plant code for the simulation and analysis of sequences in light water reactors (LWR). The main objectives of the work are the following ones: (1) the in-depth analysis of small and medium LOCA sequences in different places of a Westinghouse three-loop PWR (Almaraz NPP), with failed HPSI, regarding important parameters, such as break size or delay in operator response; (2) obtainment and analysis of Damage Domains related to LOCA transients in PWRs, according to ISA methodology; and (3) review some of the results of generic safety analyses for LOCA sequences in those conditions. The results of the thesis cover three separated areas: (a) the physical phenomenology of the sequences under study; (b) the conclusions of LOCA safety analyses; and (c) the importance of consequences of human actions by the operating crew. These results, in turn, are of two main types: (1) endorsement of previous knowledge about this kind of sequences, which is included in the literature; and (2) findings in each of the three aforementioned areas, not reported in the reviewed literature. In short, the results of this thesis support the use of ISA-like methodology as an alternative method for systematic analysis of LWR accidental sequences.
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Nowadays, the analysis of the X-ray spectra of magnetically powered neutron stars or magnetars is one of the most valuable tools to gain insight into the physical processes occurring in their interiors and magnetospheres. In particular, the magnetospheric plasma leaves a strong imprint on the observed X-ray spectrum by means of Compton up-scattering of the thermal radiation coming from the star surface. Motivated by the increased quality of the observational data, much theoretical work has been devoted to develop Monte Carlo (MC) codes that incorporate the effects of resonant Compton scattering (RCS) in the modeling of radiative transfer of photons through the magnetosphere. The two key ingredients in this simulations are the kinetic plasma properties and the magnetic field (MF) configuration. The MF geometry is expected to be complex, but up to now only mathematically simple solutions (self-similar solutions) have been employed. In this work, we discuss the effects of new, more realistic, MF geometries on synthetic spectra. We use new force-free solutions [14] in a previously developed MC code [9] to assess the influence of MF geometry on the emerging spectra. Our main result is that the shape of the final spectrum is mostly sensitive to uncertain parameters of the magnetospheric plasma, but the MF geometry plays an important role on the angle-dependence of the spectra.
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The real-time optimization of large-scale systems is a difficult problem due to the need for complex models involving uncertain parameters and the high computational cost of solving such problems by a decentralized approach. Extremum-seeking control (ESC) is a model-free real-time optimization technique which can estimate unknown parameters and can optimize nonlinear time-varying systems using only a measurement of the cost function to be minimized. In this thesis, we develop a distributed version of extremum-seeking control which allows large-scale systems to be optimized without models and with minimal computing power. First, we develop a continuous-time distributed extremum-seeking controller. It has three main components: consensus, parameter estimation, and optimization. The consensus provides each local controller with an estimate of the cost to be minimized, allowing them to coordinate their actions. Using this cost estimate, parameters for a local input-output model are estimated, and the cost is minimized by following a gradient descent based on the estimate of the gradient. Next, a similar distributed extremum-seeking controller is developed in discrete-time. Finally, we consider an interesting application of distributed ESC: formation control of high-altitude balloons for high-speed wireless internet. These balloons must be steered into a favourable formation where they are spread out over the Earth and provide coverage to the entire planet. Distributed ESC is applied to this problem, and is shown to be effective for a system of 1200 ballons subjected to realistic wind currents. The approach does not require a wind model and uses a cost function based on a Voronoi partition of the sphere. Distributed ESC is able to steer balloons from a few initial launch sites into a formation which provides coverage to the entire Earth and can maintain a similar formation as the balloons move with the wind around the Earth.
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One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.
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Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Programa de Pós-Graduação em Geotecnia, 2015.
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The anticipated growth of air traffic worldwide requires enhanced Air Traffic Management (ATM) technologies and procedures to increase the system capacity, efficiency, and resilience, while reducing environmental impact and maintaining operational safety. To deal with these challenges, new automation and information exchange capabilities are being developed through different modernisation initiatives toward a new global operational concept called Trajectory Based Operations (TBO), in which aircraft trajectory information becomes the cornerstone of advanced ATM applications. This transformation will lead to higher levels of system complexity requiring enhanced Decision Support Tools (DST) to aid humans in the decision making processes. These will rely on accurate predicted aircraft trajectories, provided by advanced Trajectory Predictors (TP). The trajectory prediction process is subject to stochastic effects that introduce uncertainty into the predictions. Regardless of the assumptions that define the aircraft motion model underpinning the TP, deviations between predicted and actual trajectories are unavoidable. This thesis proposes an innovative method to characterise the uncertainty associated with a trajectory prediction based on the mathematical theory of Polynomial Chaos Expansions (PCE). Assuming univariate PCEs of the trajectory prediction inputs, the method describes how to generate multivariate PCEs of the prediction outputs that quantify their associated uncertainty. Arbitrary PCE (aPCE) was chosen because it allows a higher degree of flexibility to model input uncertainty. The obtained polynomial description can be used in subsequent prediction sensitivity analyses thanks to the relationship between polynomial coefficients and Sobol indices. The Sobol indices enable ranking the input parameters according to their influence on trajectory prediction uncertainty. The applicability of the aPCE-based uncertainty quantification detailed herein is analysed through a study case. This study case represents a typical aircraft trajectory prediction problem in ATM, in which uncertain parameters regarding aircraft performance, aircraft intent description, weather forecast, and initial conditions are considered simultaneously. Numerical results are compared to those obtained from a Monte Carlo simulation, demonstrating the advantages of the proposed method. The thesis includes two examples of DSTs (Demand and Capacity Balancing tool, and Arrival Manager) to illustrate the potential benefits of exploiting the proposed uncertainty quantification method.
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An Ensemble Kalman Filter is applied to assimilate observed tracer fields in various combinations in the Bern3D ocean model. Each tracer combination yields a set of optimal transport parameter values that are used in projections with prescribed CO2 stabilization pathways. The assimilation of temperature and salinity fields yields a too vigorous ventilation of the thermocline and the deep ocean, whereas the inclusion of CFC-11 and radiocarbon improves the representation of physical and biogeochemical tracers and of ventilation time scales. Projected peak uptake rates and cumulative uptake of CO2 by the ocean are around 20% lower for the parameters determined with CFC-11 and radiocarbon as additional target compared to those with salinity and temperature only. Higher surface temperature changes are simulated in the Greenland–Norwegian–Iceland Sea and in the Southern Ocean when CFC-11 is included in the Ensemble Kalman model tuning. These findings highlights the importance of ocean transport calibration for the design of near-term and long-term CO2 emission mitigation strategies and for climate projections.
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The objective of the present study was to estimate (co)variance components for length of productive life (LPL) and some alternative reproductive traits of 6-year-old Nellore cattle. The data set contained 57,410 records for age at first calving from Nellore females and was edited to remove animal records with uncertain paternity and cows with just one piece of calving information. Only animals with age at first calving ranging from 23 to 48 months and calving intervals between 11 and 24 months were kept for analysis. LPL and life production ( LP) were used to describe productive life. LPL was defined as the number of months a cow was kept in the herd until she was 6 years old, given that she was alive at first calving and LP was defined as total number of calves in that time. Four traits were used to describe reproductive traits: two breeding efficiencies on original scale were estimated using Wilcox and Tomar functions (BEW and BET, respectively), and two breeding efficiencies transformed (ASBEW and ASBET, respectively), using the function [arcsine (square root (BEi/100))]. Estimates of heritability for measures of LPL and LP were low and ranged from 0.04 to 0.05. Estimates of heritability for breeding efficiencies on original and transformed scales oscillated from 0.18 to 0.32. Estimates of genetic correlations ranged from -0.57 to 0.79 for LPL and other traits and from 0.28 to 0.63 for LP and other traits.
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In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.
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The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented
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The speed of fault isolation is crucial for the design and reconfiguration of fault tolerant control (FTC). In this paper the fault isolation problem is stated as a constraint satisfaction problem (CSP) and solved using constraint propagation techniques. The proposed method is based on constraint satisfaction techniques and uncertainty space refining of interval parameters. In comparison with other approaches based on adaptive observers, the major advantage of the presented method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements and model errors and without the monotonicity assumption. In order to illustrate the proposed approach, a case study of a nonlinear dynamic system is presented
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A traditional method of validating the performance of a flood model when remotely sensed data of the flood extent are available is to compare the predicted flood extent to that observed. The performance measure employed often uses areal pattern-matching to assess the degree to which the two extents overlap. Recently, remote sensing of flood extents using synthetic aperture radar (SAR) and airborne scanning laser altimetry (LIDAR) has made more straightforward the synoptic measurement of water surface elevations along flood waterlines, and this has emphasised the possibility of using alternative performance measures based on height. This paper considers the advantages that can accrue from using a performance measure based on waterline elevations rather than one based on areal patterns of wet and dry pixels. The two measures were compared for their ability to estimate flood inundation uncertainty maps from a set of model runs carried out to span the acceptable model parameter range in a GLUE-based analysis. A 1 in 5-year flood on the Thames in 1992 was used as a test event. As is typical for UK floods, only a single SAR image of observed flood extent was available for model calibration and validation. A simple implementation of a two-dimensional flood model (LISFLOOD-FP) was used to generate model flood extents for comparison with that observed. The performance measure based on height differences of corresponding points along the observed and modelled waterlines was found to be significantly more sensitive to the channel friction parameter than the measure based on areal patterns of flood extent. The former was able to restrict the parameter range of acceptable model runs and hence reduce the number of runs necessary to generate an inundation uncertainty map. A result of this was that there was less uncertainty in the final flood risk map. The uncertainty analysis included the effects of uncertainties in the observed flood extent as well as in model parameters. The height-based measure was found to be more sensitive when increased heighting accuracy was achieved by requiring that observed waterline heights varied slowly along the reach. The technique allows for the decomposition of the reach into sections, with different effective channel friction parameters used in different sections, which in this case resulted in lower r.m.s. height differences between observed and modelled waterlines than those achieved by runs using a single friction parameter for the whole reach. However, a validation of the modelled inundation uncertainty using the calibration event showed a significant difference between the uncertainty map and the observed flood extent. While this was true for both measures, the difference was especially significant for the height-based one. This is likely to be due to the conceptually simple flood inundation model and the coarse application resolution employed in this case. The increased sensitivity of the height-based measure may lead to an increased onus being placed on the model developer in the production of a valid model
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Random effect models have been widely applied in many fields of research. However, models with uncertain design matrices for random effects have been little investigated before. In some applications with such problems, an expectation method has been used for simplicity. This method does not include the extra information of uncertainty in the design matrix is not included. The closed solution for this problem is generally difficult to attain. We therefore propose an two-step algorithm for estimating the parameters, especially the variance components in the model. The implementation is based on Monte Carlo approximation and a Newton-Raphson-based EM algorithm. As an example, a simulated genetics dataset was analyzed. The results showed that the proportion of the total variance explained by the random effects was accurately estimated, which was highly underestimated by the expectation method. By introducing heuristic search and optimization methods, the algorithm can possibly be developed to infer the 'model-based' best design matrix and the corresponding best estimates.