Search for dissertations about: "bayesian uncertainty analysis"
Showing result 1 - 5 of 52 swedish dissertations containing the words bayesian uncertainty analysis.
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1. Robust analysis of uncertainty in scientific assessments
Abstract : Uncertainty refers to any limitation in knowledge. Identifying and characterizing uncertainty in conclusions is important to ensure transparency and avoid over or under confidence in scientific assessments. Quantitative expressions of uncertainty are less ambiguous compared to uncertainty expressed qualitatively, or not at all. READ MORE
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2. On Bayesian Decision Analysis for Evaluating Alternative Actions at Contaminated Sites
Abstract : Today, contaminated land is a widespread infrastructural problem and it is widely recognised that returning all contaminated sites to background levels, or even to levels suitable for the most sensitive land use, is not technically or financially feasible. The large number of contaminated sites and the high costs of remediation, are strong incentives for applying cost-efficient investigation and remediation strategies that consider the inherent uncertainties. READ MORE
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3. On Uncertainty and Data Worth in Decision Analysis for Contaminated Land
Abstract : Contaminated soil and groundwater is a problem that has received increased attention in the last decade. Decision-making about investigation strategies, protective actions, and remedial actions is based on sparse and uncertain information, primarily data of contaminant concentrations and geological information. READ MORE
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4. Physiologically based pharmacokinetic modeling in risk assessment - Development of Bayesian population methods
Abstract : In risk assessment of risk chemicals, variability in susceptibility in the population is an important aspect. The health hazard of a pollutant is related to the internal exposure to the chemical, i.e. the target dose, rather than the external exposure. READ MORE
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5. Uncertainty and sensitivity analysis applied to LWR neutronic and thermal-hydraulic calculations
Abstract : The deterministic modeling of LWRs begins with the computation of energy‐collapsed and homogenizedmacroscopic cross‐sections by means of a lattice code. Once these parameters are functionalized as a functionof the reactor state variables and discretized in space, they are used as input variables by core simulators inorder to calculate the spatial distribution of the neutron flux and thus, the spatial distribution of the power. READ MORE