Search results for "Uncertainty estimation"

Daily streamlow prediction with uncertainty in ephemeral catchments using the GLUE methodology

2009

Abstract The Generalised Likelihood Uncertainty Estimation (GLUE) approach is presented here as a tool for estimating the predictive uncertainty of a rainfall–runoff model. The GLUE methodology allows to recognise the possible equifinality of different parameter sets and assesses the likelihood of a parameters set being acceptable simulator when model predictions are compared to observed field data. The results of the GLUE methodology depend greatly on the choice of the likelihood measure and on the choice of the threshold which determines if a parameters set is behavioural or not. Moreover the sampling size has a strong influence on the uncertainty assessment of the response of a rainfall–…

comparing two start-up strategies for MBRs: experimental study and mathematical modelling

2012

Abstract The performance of a membrane bioreactor (MBR), and mechanisms of fouling formation, may differ due to the start-up. Therefore, the start-up can constitute an aspect that critically influences MBR performance during its lifespan. Indeed, the start-up can influence the mechanisms of membrane fouling, which is of paramount importance in an MBR. In order to gain insights on the effects of the start-up, both experimental and mathematical modelling studies were carried out on an MBR pilot plant. The MBR pilot plant constituted of a hollow fibre membrane module, in a submerged configuration, was fed by real wastewater. Two experimental periods were carried out, lasting 65 days each, char…

Uncertainty estimation of a complex water quality model: The influence of Box–Cox transformation on Bayesian approaches and comparison with a non-Bay…

2012

Abstract In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised L…

Sensitivity and uncertainty analysis of an integrated membrane bioreactor model

2015

Sensitivity and uncertainty analysis, although can be of primarily importance in mathematical modelling approaches, are scarcely applied in the field of membrane bioreactor (MBR). An integrated mathematical model for MBR is applied with the final aim to pin down sources of uncertainty in MBR modelling. The uncertainty analysis has been performed combining global sensitivity analysis (GSA) with the generalized likelihood uncertainty estimation (GLUE). The model and methodology were applied to a University Cape Town pilot plant. Results show that the complexity of the modelled processes and the propagation effect from the influent to the effluent increase the uncertainty of the model predicti…

Virtual Instruments: Uncertainty Evaluation in the Presence of Electromagnetic Interferences

2007

The electromagnetic interferences can influence the performances of a virtual instrument; consequently, in a generic measurement performed by using these instruments, the related uncertainty values can increase. In the paper, we report the results of various experimental tests performed with the aim to check if and how the radiated and/or conducted disturbances affect the instruments' characteristics and, in particular, the single uncertainty sources. Starting from these results and applying an already proposed method for the uncertainty estimation in the measurements performed by means of virtual instruments, it is possible to take into account and to evaluate the contribute of the electro…

Uncertainty management in the measurements for the electric power quality analysis

2014

The paper deals with the uncertainty estimation in the measurements performed to assess the electric power quality. In a first steps, all the error sources, which give a significant contribution to the combined uncertainty associated to the measurement results, are identified. Successively, in order to analyze how the errors combine and propagate through the measurement chain, four approaches are proposed and validated. These approaches entail a greater and greater uncertainty overestimation, but, at the same time, require less and less time and resources. Therefore, the four methodologies are perfectly adequate for the implementation of the PUMA (Procedure for Uncertainty Management) metho…

Uncertainty in urban stormwater quality modelling: The influence of likelihood measure formulation in the GLUE methodology

2009

In the last years, the attention on integrated analysis of sewer networks, wastewater treatment plants and receiving waters has been growing. However, the common lack of data in the urban water-quality field and the incomplete knowledge regarding the interpretation of the main phenomena taking part in integrated urban water systems draw attention to the necessity of evaluating the reliability of model results. Uncertainty analysis can provide useful hints and information regarding the best model approach to be used by assessing its degrees of significance and reliability. Few studies deal with uncertainty assessment in the integrated urban-drainage field. In order to fill this gap, there ha…

ERROR AND UNCERTAINTY ANALYSIS OF RESIDUAL STRESS EVALUATION BY USINGTHE RING-CORE METHOD

2014

The Ring-Core Method is a technique used for the experimental analysis of the residual stresses in mechanical components. For uniform and non-uniform residual stresses estimation, the use of the method leads in general to accurate results but, unfortunately at present the user does not have appropriate procedures to correct the obtained results from systematic errors as well as to estimate the uncertainty due to random errors. In order to overcome such drawbacks, in the present work, the procedures for the correction of the effects of the main error sources and for the stress uncertainty estimation, are proposed. The practical application of such procedures allow the user to highlight the r…

How to Deal with Systematic Uncertainties

2013

Urban runoff modelling uncertainty: Comparison among Bayesian and pseudo-Bayesian methods

2009

Urban stormwater quality modelling plays a central role in evaluation of the quality of the receiving water body. However, the complexity of the physical processes that must be simulated and the limited amount of data available for calibration may lead to high uncertainty in the model results. This study was conducted to assess modelling uncertainty associated with catchment surface pollution evaluation. Eight models were compared based on the results of a case study in which there was limited data available for calibration. Uncertainty analysis was then conducted using three different methods: the Bayesian Monte Carlo method, the GLUE pseudo-Bayesian method and the GLUE method revised by m…