Search results for "uncertainty."
showing 10 items of 972 documents
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…
Consistent measurements of alpha(s) from precise oriented event shape distributions
2000
An updated analysis using about 1.5 million events recorded at $\sqrt{s} = M_Z$ with the DELPHI detector in 1994 is presented. Eighteen infrared and collinear safe event shape observables are measured as a function of the polar angle of the thrust axis. The data are compared to theoretical calculations in ${\cal O} (\alpha_s^2)$ including the event orientation. A combined fit of $\alpha_s$ and of the renormalization scale $x_{\mu}$ in $\cal O(\alpha_s^2$) yields an excellent description of the high statistics data. The weighted average from 18 observables including quark mass effects and correlations is $\alpha_s(M_Z^2) = 0.1174 \pm 0.0026$. The final result, derived from the jet cone energ…
R&D alliances timing under uncertainty: from theory toward experiments
2015
There is a growing awareness that managers have cognitive biases when making investments decisions under uncertainty. There is evidence of deviation from the predictions derived using normative models, such as real options models. The proposed research sheds light on the importance of integrating normative models with experimental methods in order to predict and explain such cognitive limitations. To this aim, starting from a real options model dealing with alliance timing decisions, we propose a simple design of an experiment, that can been used to test some of the fundamental insights of real options theory in the context of R&D alliances.
Monte Carlo dosimetric study of the medium dose rate CSM40 source
2013
Abstract The 137Cs medium dose rate (MDR) CSM40 source model (Eckert & Ziegler BEBIG, Germany) is in clinical use but no dosimetric dataset has been published. This study aims to obtain dosimetric data for the CSM40 source for its use in clinical practice as required by the American Association of Physicists in Medicine (AAPM) and the European Society for Radiotherapy and Oncology (ESTRO). Penelope2008 and Geant4 Monte Carlo codes were used to characterize this source dosimetrically. It was located in an unbounded water phantom with composition and mass density as recommended by AAPM and ESTRO. Due to the low photon energies of 137Cs, absorbed dose was approximated by collisional kerma. Add…
A Bayesian approach to assess data from radionuclide activity analyses in environmental samples
2007
A Bayesian statistical approach is introduced to assess experimental data from the analyses of radionuclide activity concentration in environmental samples (low activities). A theoretical model has been developed that allows the use of known prior information about the value of the measurand (activity), together with the experimental value determined through the measurement. The model has been applied to data of the Inter-laboratory Proficiency Test organised periodically among Spanish environmental radioactivity laboratories that are producing the radiochemical results for the Spanish radioactive monitoring network. A global improvement of laboratories performance is produced when this pri…
Influence of rating curve uncertainty on daily rainfall–runoff model predictions
2005
River discharge observations are usually affected by uncertainty, which is due to many concurrent causes and strongly affects the response of rainfall-runoff models. The present paper is aimed at studying the influence of imperfect rating curve knowledge on the uncertainty of the response of a daily conceptual linear-nonlinear rainfall-runoff model. To describe the impact of imperfect rating curve knowledge, simulations have been conducted using a conceptual rainfall-runoff model and continuous daily series of rainfall, air temperature and discharges recorded in a Sicilian catchment. The GLUE procedure was used to introduce the uncertainty of the rating curve in a classical rainfall-runoff …
Models of Dynamical Modelling Under Uncertainty
1986
The objective of this work is to modelize the evolution of a Model-System to be adapted to a Random System. This evolution is described by means of the change of a probabilistic function, through deterministic rules and in function of the random responses of the modelized System. This probabilistic function can describe the relative weight of distinct submodels (deterministic or random Systems, with constant or variable stimulus), or the stimulus-response relation in the Model-System (Adaptative Random System). We conclude that the Adaptative Random Model permits a more precise, simple and economical modelling.
Assessment of building energy modelling studies to meet the requirements of the new Energy Performance of Buildings Directive
2020
Abstract The cost optimal method (COM) as applied in the Energy Performance of Buildings Directive (EPBD) uses “non-calibrated deterministic reference buildings (RBs)”. Such RBs are defined with single envelope and equipment parameter values, for which calibration with actual building stock energy performance (EP) is not undertaken. Thus, it is not possible to visualise the effect of uncertainties or diversity in the input parameters on cost-optimal level benchmarks and to verify the choice of RBs. The paper proposes an update to the COM via use of “Probabilistic Bayesian calibrated RBs” to handle uncertainties and produce more realistic cost optimal levels to support policy makers in devis…
Handling epistemic uncertainty in the Fault Tree Analysis using interval valued expert information
2014
Risk Analysis ( RA) is a meaningful process in every industrial context, particularly referring to major hazard plants. In such sites, input reliability data are generally poor so leading to a partial or incomplete knowledge of the failure process. As a consequence, RA is always affected by the so called epistemic uncertainty which presence makes inappropriate the classical probabilistic approach. Therefore, the present work deals with such a kind of uncertainty in the Fault Tree Analysis (FTA) and proposes a new aggregation rule to combine the interval-valued information supplied by a team of experts about each Basic Event ( BE). The aggregation leads to an interval which bounds are modell…
A bottom-up procedure to calculate the Top Event probability in presence of epistemic uncertainty
2012
Industrial plants may be subjected to very dangerous events. Different methodologies are employed to evaluate the probability of their occurrence, as Process Safety Analysis (PSA) or Risk Analysis (RA). However, since for rare events reliability data are poor, the epistemic uncertainty needs to be considered. In this context, the classical probabilistic approach cannot be successfully used and then different approaches must be taken into account. Actually, this paper proposes the use of the Evidence Theory or Dempster-Shafer Theory (DST) to deal with data characterizing rare events in high risk industrial sites. In particular, a classical Fault Tree Analysis (FTA) is considered when the onl…