Examinando por Materia "Uncertainty analysis"
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Ítem An alternative model to explain the vectorial capacity using as example Aedes aegypti case in dengue transmission(Elsevier BV, 2019-01-01) Catano-Lopez A.; Rojas-Diaz D.; Laniado H.; Arboleda-Sánchez S.; Puerta-Yepes M.E.; Lizarralde-Bejarano D.P.; Catano-Lopez A.; Rojas-Diaz D.; Laniado H.; Arboleda-Sánchez S.; Puerta-Yepes M.E.; Lizarralde-Bejarano D.P.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y AplicacionesVectorial capacity (VC), as a concept that describes the potential of a vector to transmit a pathogen, has had historical problems related to lacks in dimensional significance and high error propagation from parameters that take part in the model to output. Hence, values estimated with those equations are not sufficiently reliable to consider in control strategies or vector population study. In this paper, we propose a new VC model consistent at dimensional level, i.e., the definition and the equation of VC have same and consistent units, with a parameter estimation method and mathematical structure that reduces the uncertainty in model output, using as a case of study an Aedes aegypti population of the municipality of Bello, Colombia. After a literature review, we selected one VC equation following biological, measurability and dimensional criteria, then we rendered a local and global sensitivity analysis, identifying the mortality rate of mosquitoes as a target component of the equation. Thus, we studied the Weibull and Exponential distributions as probabilistic models that represent the expectation of mosquitoes infective life, intending to include the best distribution in a selected VC structure. The proposed mortality rate estimation method includes a new parameter that represents an increase or decrease in vector mortality, as it may apply. We noticed that its estimation reduces the uncertainty associated with the expectation of mosquitoes' infective life expression, which also reduces the output range and variance in almost a half. Virology; Applied mathematics; Health sciences; Epidemiology; Infectious disease; Mortality; Uncertainty analysis; Vectorial capacity; Sensitivity analysis; Dengue © 2019 The AuthorsÍtem An alternative model to explain the vectorial capacity using as example Aedes aegypti case in dengue transmission(Elsevier BV, 2019-01-01) Catano-Lopez A.; Rojas-Diaz D.; Laniado H.; Arboleda-Sánchez S.; Puerta-Yepes M.E.; Lizarralde-Bejarano D.P.; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoVectorial capacity (VC), as a concept that describes the potential of a vector to transmit a pathogen, has had historical problems related to lacks in dimensional significance and high error propagation from parameters that take part in the model to output. Hence, values estimated with those equations are not sufficiently reliable to consider in control strategies or vector population study. In this paper, we propose a new VC model consistent at dimensional level, i.e., the definition and the equation of VC have same and consistent units, with a parameter estimation method and mathematical structure that reduces the uncertainty in model output, using as a case of study an Aedes aegypti population of the municipality of Bello, Colombia. After a literature review, we selected one VC equation following biological, measurability and dimensional criteria, then we rendered a local and global sensitivity analysis, identifying the mortality rate of mosquitoes as a target component of the equation. Thus, we studied the Weibull and Exponential distributions as probabilistic models that represent the expectation of mosquitoes infective life, intending to include the best distribution in a selected VC structure. The proposed mortality rate estimation method includes a new parameter that represents an increase or decrease in vector mortality, as it may apply. We noticed that its estimation reduces the uncertainty associated with the expectation of mosquitoes' infective life expression, which also reduces the output range and variance in almost a half. Virology; Applied mathematics; Health sciences; Epidemiology; Infectious disease; Mortality; Uncertainty analysis; Vectorial capacity; Sensitivity analysis; Dengue © 2019 The AuthorsÍtem Development of structural debris flow fragility curves (debris flow buildings resistance) using momentum flux rate as a hazard parameter(Elsevier B.V., 2018-05-18) Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Universidad EAFIT. Departamento de Ingeniería de Producción; Materiales de IngenieríaSocietal risks associated with debris flow hazards are significant and likely to escalate due to global population growth trends and the compounding effects of climate change. Quantitative risk assessment methods (QRA) provide a means of anticipating the likely impacts and consequences of settlement in areas susceptible to landslide activity and are increasingly being used to inform land use decisions that seek to increase disaster resilience through mitigation and/or adaptation. Current QRA methods for debris flow hazards are based primarily on empirical vulnerability functions that relate hazard intensity (depth, velocity, etc.) to expected levels of loss for a given asset of concern, i.e. most of current methods are dedicated to loss-intensity relations. Though grounded in observed cause-effect relationships, empirical vulnerability functions are not designed to predict the capacity of a building to withstand the physical impacts of a debris flow event, or the related uncertainties associated with modelling building performance as a function of variable debris flow parameters. This paper describes a methodology for developing functions that relate hazard intensity to probability of structural damage, i.e., fragility functions, rather than vulnerability functions, based on the combined hydrodynamic forces of a debris flow event (hazard level) and the inherent structural resistance of building typologies that are common in rural mountainous settings (building performance). Hazard level includes a hydrodynamic force variable (FDF), which accounts for the combined effects of debris flow depth and velocity, i.e. momentum flux (hv2), material density (?) and related flow characteristics including drag (Cd) and impact coefficient (Kd). Building performance is measured in terms of yield strength (Ay), ultimate lateral capacity (AU) and weight to breadth ratios (W/B) defined for a portfolio building types that are common in mountain settlements. Collectively, these model parameters are combined using probabilistic methods to produce building-specific fragility functions that describe the probability of reaching or exceeding successive thresholds of structural damage over a range of hazard intensity values, expressed in terms of momentum flux. Validation of the proposed fragility model is based on a comparison between model outputs and observed cause-effect relationships for recent debris flow events in South Korea and in Colombia. Debris flow impact momentum fluxes, capable of resulting in complete damage to unreinforced masonry buildings (URM) in those regions are estimated to be on the order of 24 m3/s2, consistent with field-based observations. Results of our study offer additional capabilities for assessing risks associated with urban growth and development in areas exposed to debris flow hazards. © 2018 Elsevier B.V.Ítem Development of structural debris flow fragility curves (debris flow buildings resistance) using momentum flux rate as a hazard parameter(Elsevier B.V., 2018-05-18) Prieto, Jorge Alonso; Journeay, Murray; Acevedo A.B.; Arbelaez, Juan; Ulmi, Malaika; Mecánica AplicadaSocietal risks associated with debris flow hazards are significant and likely to escalate due to global population growth trends and the compounding effects of climate change. Quantitative risk assessment methods (QRA) provide a means of anticipating the likely impacts and consequences of settlement in areas susceptible to landslide activity and are increasingly being used to inform land use decisions that seek to increase disaster resilience through mitigation and/or adaptation. Current QRA methods for debris flow hazards are based primarily on empirical vulnerability functions that relate hazard intensity (depth, velocity, etc.) to expected levels of loss for a given asset of concern, i.e. most of current methods are dedicated to loss-intensity relations. Though grounded in observed cause-effect relationships, empirical vulnerability functions are not designed to predict the capacity of a building to withstand the physical impacts of a debris flow event, or the related uncertainties associated with modelling building performance as a function of variable debris flow parameters. This paper describes a methodology for developing functions that relate hazard intensity to probability of structural damage, i.e., fragility functions, rather than vulnerability functions, based on the combined hydrodynamic forces of a debris flow event (hazard level) and the inherent structural resistance of building typologies that are common in rural mountainous settings (building performance). Hazard level includes a hydrodynamic force variable (FDF), which accounts for the combined effects of debris flow depth and velocity, i.e. momentum flux (hv2), material density (?) and related flow characteristics including drag (Cd) and impact coefficient (Kd). Building performance is measured in terms of yield strength (Ay), ultimate lateral capacity (AU) and weight to breadth ratios (W/B) defined for a portfolio building types that are common in mountain settlements. Collectively, these model parameters are combined using probabilistic methods to produce building-specific fragility functions that describe the probability of reaching or exceeding successive thresholds of structural damage over a range of hazard intensity values, expressed in terms of momentum flux. Validation of the proposed fragility model is based on a comparison between model outputs and observed cause-effect relationships for recent debris flow events in South Korea and in Colombia. Debris flow impact momentum fluxes, capable of resulting in complete damage to unreinforced masonry buildings (URM) in those regions are estimated to be on the order of 24 m3/s2, consistent with field-based observations. Results of our study offer additional capabilities for assessing risks associated with urban growth and development in areas exposed to debris flow hazards. © 2018 Elsevier B.V.Ítem Full scale fatigue test performed to the bolster beam of a railway vehicle(Springer-Verlag France, 2018-02-01) Gutiérrez-Carvajal, R.E.; Betancur, G.R.; Barbosa, J.; Castañeda, L.F.; Zaja¸c, G.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)Many structural elements are exposed to conditions of load that are difficult to consider during the design stage, such as environment uncertainties, random impacts, overloads and inherent material idealization amongst others, hence, miss-estimating its life-time cycle. One way to test those designs is to construct a representative full-scale specimen and test it under the most critical load conditions in a controlled laboratory. Herein, we present a case of study of the fatigue test performed over a bolster beam redesigned in Universidad EAFIT belonging to a railway vehicle. The test was composed by three stages, each one testing a different load hypothesis. The bolster beam was instrumented at the most critical locations, following the results of a FEM analysis previously computed. As results, the most critical welds were identified and the total damage computed for an equivalent operation of eighteen-years, and also the behaviour of the specimen in presence of extreme longitudinal loads. © 2016, Springer-Verlag France.Ítem Full scale fatigue test performed to the bolster beam of a railway vehicle(Springer-Verlag France, 2018-02-01) Gutiérrez-Carvajal, R.E.; Betancur, G.R.; Barbosa, J.; Castañeda, L.F.; Zaja¸c, G.; Gutiérrez-Carvajal, R.E.; Betancur, G.R.; Barbosa, J.; Castañeda, L.F.; Zaja¸c, G.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Mecatrónica y Diseño de MáquinasMany structural elements are exposed to conditions of load that are difficult to consider during the design stage, such as environment uncertainties, random impacts, overloads and inherent material idealization amongst others, hence, miss-estimating its life-time cycle. One way to test those designs is to construct a representative full-scale specimen and test it under the most critical load conditions in a controlled laboratory. Herein, we present a case of study of the fatigue test performed over a bolster beam redesigned in Universidad EAFIT belonging to a railway vehicle. The test was composed by three stages, each one testing a different load hypothesis. The bolster beam was instrumented at the most critical locations, following the results of a FEM analysis previously computed. As results, the most critical welds were identified and the total damage computed for an equivalent operation of eighteen-years, and also the behaviour of the specimen in presence of extreme longitudinal loads. © 2016, Springer-Verlag France.Ítem Influence of energy consumption on battery sizing of electric fluvial vessels: a Colombian Case Study(Institute of Electrical and Electronics Engineers Inc., 2020-09-12) Giraldo, E.; Gaviria, Gregorio; Betancur E.; Gómez, G.O.; Mejá-Gutiérrez, R.; Giraldo, E.; Gaviria, Gregorio; Betancur E.; Gómez, G.O.; Mejá-Gutiérrez, R.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)Electric vessels represent a sustainable solution for fluvial mobility. However, their energy demand is higher compared to terrestrial vehicles, so that, increasing the hydrodynamic efficiency is mandatory.Ítem Simulation of non-stationary non-Gaussian random fields from sparse measurements using Bayesian compressive sampling and Karhunen-Loève expansion(Elsevier BV, 2019-03-20) Montoya, S.; Tengyuan Zhao; Yue Hu; Yu Wang; Kok-Kwang Phoon; Mecánica AplicadaThe first step to simulate random fields in practice is usually to obtain or estimate random field parameters, such as mean, standard deviation, correlation function, among others. However, it is difficult to estimate these parameters, particularly the correlation length and correlation functions, in the presence of sparse measurement data. In such cases, assumptions are often made to define the probabilistic distribution and correlation structure (e.g. Gaussian distribution and stationarity), and the sparse measurement data are only used to estimate the parameters tailored by these assumptions. However, uncertainty associated with the degree of imprecision in this estimation process is not taken into account in random field simulations. This paper aims to address the challenge of properly simulating non-stationary non-Gaussian random fields, when only sparse data are available. A novel method is proposed to simulate non-stationary and non-Gaussian random field samples directly from sparse measurement data, bypassing the difficulty in random field parameter estimation from sparse measurement data. It is based on Bayesian compressive sampling and Karhunen–Loève expansion. First, the formulation of the proposed generator is described. Then, it is illustrated through simulated examples, and tested with wind speed time series data. The results show that the proposed method is able to accurately depict the underlying spatial correlation from sparse measurement data for both non-Gaussian and non-stationary random fields. In addition, the proposed method is able to quantify the uncertainty related to random field parameter estimation from the sparse measurement data and propagate it to the generated random field. © 2019 Elsevier LtdÍtem Towards a holistic framework to model epidemics in presence of uncertainty : formulation of mathematical models and estimation of confidence intervals(Universidad EAFIT, 2021) Rojas Díaz, Daniel; Vélez Sánchez, Carlos Mario; Puerta Yepes, María Eugenia; Cadavid Moreno, Carlos AlbertoÍtem Wind turbine selection method based on the statistical analysis of nominal specifications for estimating the cost of energy(Elsevier Ltd, 2018-10-15) Arias-Rosales, A.; Osorio-Gómez, G.; Universidad EAFIT. Departamento de Ingeniería de Diseño; Ingeniería de Diseño (GRID)Wind turbine selection is a critical engineering problem in the overall cost-effectiveness of a wind project. With the wide spreading and democratization of wind energy technologies, non-expert stakeholders are being faced with the challenge of selecting among very different wind turbines. As a comprehensive indicator, the cost of energy can serve as a guide, but reportedly misleading publicity and commonly unavailable information render its calculation more inaccessible and less reliable. Accordingly, this work proposes a method to compare wind turbines, on the basis of the cost of energy, from only nominal specifications and a standard characterization of the local wind conditions. For this endeavor, it was identified that two key variables are not usually available at a preliminary stage: the total efficiency and a feasible hub height. Through a systematic statistical analysis of the trends in a constructed dataset of 176 turbines, it was possible to establish regression models for the estimation of both variables. These models were tested in a validation set and their estimations were found to correctly characterize the central trend of the data without significant deviations. The uncertainty related to the use of both models was addressed by analyzing the 95% Prediction Intervals and the stochastic rank dominance. The established statistical models were then used as the core of the proposed selection method. When the available information is limited or not trustworthy, the steps of the method can be followed as an approach to estimate the cost of energy of a given horizontal axis wind turbine in a given location. © 2018 Elsevier Ltd