Search results for "Uncertainty analysis"

Uncertainty propagation throughout an integrated water-quality model

2010

In integrated urban drainage water quality models, due to the fact that integrated approaches are basically a cascade of sub-models (simulating sewer system, wastewater treatment plant and receiving water body), uncertainty produced in one sub-model propagates to the following ones depending on the model structure, the estimation of parameters and the availability and uncertainty of measurements in the different parts of the system. Uncertainty basically propagates throughout a chain of models in which simulation output from upstream models is transferred to the downstream ones as input. The overall uncertainty can differ from the simple sum of uncertainties generated in each sub-model, dep…

Quantifying sensitivity and uncertainty analysis of a new mathematical model for the evaluation of greenhouse gas emissions from membrane bioreactors

2015

Abstract A new mathematical model able to quantify greenhouse gas (GHG) emissions in terms of carbon dioxide (CO 2 ) and nitrous oxide (N 2 O) for a Membrane Bioreactor (MBR) is presented. The proposed mathematical model is of the Activated Sludge Model (ASM) family and takes into account simultaneously both biological and physical processes (e.g., membrane fouling). An analysis of the key factors and sources of uncertainty influencing GHG emissions is also presented. Specifically, the standardized regression coefficient, the Extended-FAST and a Monte Carlo based method are employed for assessing model factors which influence three performance indicators: effluent quality index, operational…

A mathematical model for a sequential batch membrane bioreactor pilot plant

2016

A mathematical model to quantify the nitrogen removal for a membrane bioreactor (MBR) has been presented in this study. The model has been applied to a pilot plant having a pre-denitrification MBR scheme. The pilot plant was cyclically filled with real saline wastewater according to the fill-draw-batch operation. The model was calibrated by adopting a specific protocol based on extensive field dataset. The Standardized Regression Coefficient (SRC) method was adopted to select the most influential model factors to be calibrated. Results related to the SRC method have shown that model factors of the efficiency of backwashing and the biological factors affecting the soluble microbial products …

ERROR AND UNCERTAINTY ANALYSIS OF THE RESIDUAL STRESSES COMPUTED BY USING THE HOLE DRILLING METHOD

2011

The hole-drilling method is one of the most used techniques for the experimental analysis of the residual stresses in mechanical components. For both through-thickness uniform and non-uniform residual stresses, its practical application is standardised by the ASTM E837-08. For uniform residual stresses, to which the present work deals with, the use of the method in accordance with the ASTM limitations, leads to results with a bias of about 10%. Unfortunately, although some experimental parameters can be frequently out of the corresponding standard limitation, the user does not have appropriate procedures to correct the obtained results which, in accordance with the ASTM standard, have to be…

Latin hypercube sampling with inequality constraints

2010

International audience; In some studies requiring predictive and CPU-time consuming numerical models, the sampling design of the model input variables has to be chosen with caution. For this purpose, Latin hypercube sampling has a long history and has shown its robustness capabilities. In this paper we propose and discuss a new algorithm to build a Latin hypercube sample (LHS) taking into account inequality constraints between the sampled variables. This technique, called constrained Latin hypercube sampling (cLHS), consists in doing permutations on an initial LHS to honor the desired monotonic constraints. The relevance of this approach is shown on a real example concerning the numerical w…

Assessment of Modelling Structure and Data Availability Influence on Urban Flood Damage Modelling Uncertainty

2014

Abstract In modelling application, different model structures may be equally reliable in terms of calibration ability but they may produce different uncertainty levels; moreover, available data during model calibration may influence the uncertainty linked to the predictions of the same modelling structure. In the present paper, Bayesian model-averaging was applied to several flood damage estimation models in order to identify the best model combination for urban flooding distribution analysis in Palermo city center (Italy). During the analysis, was taken into account the effect of the available data growth on the model uncertainty with respect to the different combination of models outputs.

How to Deal with Systematic Uncertainties

2013

EPPS16 - First nuclear PDFs to include LHC data

2017

We present results of our recent EPPS16 global analysis of NLO nuclear parton distribution functions (nPDFs). For the first time, dijet and heavy gauge boson production data from LHC proton-lead collisions have been included in a global fit. Especially, the CMS dijets play an important role in constraining the nuclear effects in gluon distributions. With the inclusion of also neutrino-nucleus deeply-inelastic scattering and pion-nucleus Drell-Yan data and a proper treatment of isospin-corrected data, we were able to free the flavor dependence of the valence and sea quark nuclear modifications for the first time. This gives us less biased, yet larger, flavor by flavor uncertainty estimates. …

Continuous Discharge Monitoring Using Non-contact Methods for Velocity Measurements: Uncertainty Analysis

2014

At gauged site, water stage and discharge hydrographs can be related also during unsteady flow conditions, using the one-dimensional diffusive hydraulic model, DORA, and exploiting sporadic surface velocity measurements carried out with a radar sensor, during the rising limb of the flood. Indeed, starting from the measured surface velocity, the application of a simplified entropic velocity distribution model allows obtaining the benchmark discharge for the Manning’s roughness calibration. The aim of this work is twofold. First, to address the uncertainty of the approach. Second, to detect the minimum water level along the rising limb in which the occasional surface velocity measurement shou…

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…