Search results for " Uncertainty"
showing 10 items of 777 documents
Uncertainty evaluation of a Backward/Forward Load Flow algorithm for a MV smart grid
2015
This paper presents the uncertainty evaluation of an innovative measurement algorithm for load flow analysis in MV distribution networks. The measurement procedure is based on Low Voltage (LV) load power measurements applied on a Backward/Forward (B/F) algorithm for the Load Flow (LF) resolution. Furthermore, in the procedure a three phase voltage measurement at the MV generating substation bus-bars is also considered. The accuracy analysis of the LF algorithm is performed in the case of a real load condition in the distribution grid of Ustica island, Italy. The analysis takes into account the uncertainty of the measurement instruments at the LV side of each secondary substation power trans…
Integrated urban water modelling with uncertainty analysis
2006
In the last twenty years, the scientific world has paid particular care towards the problems that involve the environment. Accordingly, several researches were developed to describe phenomena that take place during both wet and dry periods and to increase the knowledge in this field. In particular, attention was addressed towards the problems linked with receiving water body pollution because of the impact of rain water in the urban environment. In order to obtain a good description of the problem, it is important to analyse both quantity and quality aspects connected with all the transformation phases that characterise the urban water cycle. Today, according to this point, integrated model…
The influence of rainfall time resolution for urban water quality modelling
2010
The objective of this paper is the definition of a methodology to evaluate the impact of the temporal resolution of rainfall measurements in urban drainage modelling applications. More specifically the effect of the temporal resolution on urban water quality modelling is detected analysing the uncertainty of the response of rainfall–runoff modelling. Analyses have been carried out using historical rainfall–discharge data collected for the Fossolo catchment (Bologna, Italy). According to the methodology, the historical rainfall data are taken as a reference, and resampled data have been obtained through a rescaling procedure with variable temporal windows. The shape comparison between ‘true’…
Greenhouse gases from membrane bioreactors: Mathematical modelling, sensitivity and uncertainty analysis
2017
In this study a new mathematical model to quantify greenhouse gas emissions (namely, carbon dioxide and nitrous oxide) from membrane bioreactors (MBRs) is presented. The model has been adopted to predict the key processes of a pilot plant with pre-denitrification MBR scheme, filled with domestic and saline wastewater. The model was calibrated by adopting an advanced protocol based on an extensive dataset. In terms of nitrous oxide, the results show that an important role is played by the half saturation coefficients related to nitrogen removal processes and the model factors affecting the oxygen transfer rate in the aerobic and MBR tanks. Uncertainty analysis showed that for the gaseous mod…
Handling the epistemic uncertainty in the selective maintenance problem
2020
Abstract Nowadays, both continuous and discontinuous operating systems require higher and higher reliability levels in order to avoid the occurrence of dangerous or even disastrous consequences. Accordingly, the definition of appropriate maintenance policies and the identification of components to be maintained during the planned system’s downtimes are fundamental to ensure the reliability maximization. Therefore, the present paper proposes a mathematical programming formulation of the selective maintenance problem with the aim to maximize the system’s reliability under an uncertain environment. Specifically, the aleatory model related to the components’ failure process is well known, where…
A dempster-shafer theory-based approach to compute the birnbaum importance measure under epistemic uncertainty
2016
Importance Measures (IMs) aim at quantifying the contribution of components to the system performance. In Process Risk Assessment (PRA), they are commonly used by risk managers to derive information about the risk/safety significance of events. However, IMs are typically calculated without taking into account the uncertainty that inevitably occurs whenever the input reliability data are poor. In literature, uncertainty arising from the lack of knowledge on the system/process parameters is defined as epistemic or subjective uncertainty. The present work aims at investigating on its influence on the Birnbaum IM and on how such an uncertainty could be accounted for in the components ranking. I…
An easy-to-use model for O2 supply to red muscle. Validity of assumptions, sensitivity to errors in data
1995
An easy-to-use capillary cylinder model of O2 supply to muscle is presented that considers all those factors that are known to be most important for realistic results: (1) red blood cell (RBC) O2 unloading along the capillary, (2) effects of the particulate nature of blood, (3) free and hemoglobin-facilitated O2 diffusion and reaction kinetics inside RBCs, (4) free and myoglobin-facilitated O2 diffusion inside the muscle cell, and (5) carrier-free region separating RBC and tissue. In a first approach, a highly simplified yet reasonably accurate treatment of the complex three-dimensional oxygen diffusion field in and next to capillaries is employed. As an alternative, a more realistic descri…
Past price “memory” in the housing market: testing the performance of different spatio-temporal specifications.
2017
ABSTRACTRecent methodological developments provide a way to incorporate the temporal dimension when accounting for spatial effects in hedonic pricing. Weight matrices should decompose the spatial effects into two distinct components: bidirectional contemporaneous spatial connections; and unidirectional spatio-temporal effects from past transactions. Our iterative estimation approach explicitly analyses the role of time in price determination. The results show that both spatio-temporal components should be included in model specification; past transaction information stops contributing to price determination after eight months; and limited temporal friction is exhibited within this period. T…
ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19
2022
The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing como…
On the use of approximate Bayesian computation Markov chain Monte Carlo with inflated tolerance and post-correction
2020
Approximate Bayesian computation allows for inference of complicated probabilistic models with intractable likelihoods using model simulations. The Markov chain Monte Carlo implementation of approximate Bayesian computation is often sensitive to the tolerance parameter: low tolerance leads to poor mixing and large tolerance entails excess bias. We consider an approach using a relatively large tolerance for the Markov chain Monte Carlo sampler to ensure its sufficient mixing, and post-processing the output leading to estimators for a range of finer tolerances. We introduce an approximate confidence interval for the related post-corrected estimators, and propose an adaptive approximate Bayesi…